Mathew K AnalyticsLearn Python & Data Analytics by doing
702 free Python, data analytics and machine learning video lessons with downloadable Jupyter notebooks and 86 real datasets. Learn pandas, NumPy, scikit-learn, SQL, FastAPI and more.
702 video lessons30 free courses86 datasets
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Real-World Data Analytics 26Data analytics zero to hero 30Pandas Projects 10Python for Data Analysts 12Full-Length Courses 7Python data types deep dive 12Python standard library deep dive 24Statistics for data analysts 15ML algorithms deep dive 12Scikit-learn deep dive 18FastAPI deep dive 12Market Research Analytics in Python 56Mastering Pandas 44Python for Retail E-commerce Analytics 43Social Media Content Analytics 41Python for Data Science 38Probability and Statistics in python 35Data visualisation in python 34Data Science Projects 33Data Mining 31Python For Time Series 30Supply Chain Operations Analytics 27Python for Banking and Finance 24Python Fundamentals 22Finance and Stock Market Analytics 16Python For Machine Learning 16OpenAI 14Python library centre 11Python Libraries 6Pandas 3
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28 minLesson 1
Python Data Analytics #01: Acquiring & Auditing a Real Retail Dataset (Pandas Tutorial)
28 minLesson 2
Python Data Analytics #02: Customer Segmentation with RFM Analysis in Python
29 minLesson 3
Python Data Analytics #03: Market Basket Analysis & Association Rules in Python
28 minLesson 4
Python Data Analytics #04: Cohort Analysis & Customer Retention in Python
29 minLesson 5
Python Data Analytics #05: Sales Forecasting for Retail Demand in Python
30 minLesson 6
Python Data Analytics #06: Price & Discount Impact Analysis in Python
29 minLesson 7
Python Data Analytics #07: Customer Lifetime Value (CLV) Modelling in Python
28 minLesson 8
Python Data Analytics #08: Product Category Performance & ABC Analysis in Python
29 minLesson 9
Python Data Analytics #09: Web Scraping Real Product Prices for Competitor Analysis
29 minLesson 10
Python Data Analytics #10: Retail Analytics Capstone — End-to-End Report in Python
27 minLesson 11
Python Data Analytics #11: Fetching & Cleaning Real Stock Price Data in Python
31 minLesson 12
Python Data Analytics #12: Portfolio Returns, Risk & the Efficient Frontier in Python
23 minLesson 13
Python Data Analytics #13: Technical Indicators on Real Price Series in Python
32 minLesson 14
Python Data Analytics #14: Volatility Analysis & Rolling Risk Metrics in Python
30 minLesson 15
Python Data Analytics #15: Correlation & Diversification Across Real Assets
31 minLesson 16
Python Data Analytics #16: Backtesting a Simple Trading Strategy in Python
30 minLesson 17
Python Data Analytics #17: Real Cryptocurrency Market Analysis in Python
27 minLesson 18
Python Data Analytics #18: Company Fundamentals from Real Financial Statements
31 minLesson 19
Python Data Analytics #19: Value-at-Risk & Drawdown Analysis in Python
29 minLesson 20
Python Data Analytics #20: Finance Capstone — Real Multi-Asset Portfolio Report
29 minLesson 21
Python Data Analytics #21: Scraping & Structuring Real Social Discussion Data
28 minLesson 22
Python Data Analytics #22: Sentiment Analysis on Real Text Data in Python
27 minLesson 23
Python Data Analytics #23: Real Customer Churn & Retention Analysis in Python
29 minLesson 24
Python Data Analytics #24: Marketing Campaign A/B Test Analysis in Python
28 minLesson 25
Python Data Analytics #25: Customer Funnel & Conversion Rate Analysis in Python
27 minLesson 26
Python Data Analytics #26: Analysing Real Hashtags & Topic Trends in Python
13 minLesson 1
Python Variables & Data Types Explained | Data Analytics #1
11 minLesson 2
Python Control Flow: If, For & While Loops | Data Analytics #2
11 minLesson 3
Python Functions & Modules for Reusable Code | Data Analytics #3
11 minLesson 4
Python Lists, Tuples, Sets & Dicts Explained | Data Analytics #4
13 minLesson 5
Read & Write Files in Python (CSV & TXT) | Data Analytics #5
14 minLesson 6
NumPy Arrays & Operations for Beginners | Data Analytics #6
15 minLesson 7
Pandas Series & DataFrames from Scratch | Data Analytics #7
13 minLesson 8
Pandas Data Cleaning: Missing Values & Duplicates | Data Analytics #8
11 minLesson 9
Pandas Data Wrangling: Reshape & Transform Data | Data Analytics #9
12 minLesson 10
Pandas GroupBy & Aggregation Made Simple | Data Analytics #10
12 minLesson 11
Pandas Merge, Join & Pivot Explained | Data Analytics #11
12 minLesson 12
Pandas Time Series Analysis Tutorial | Data Analytics #12
10 minLesson 13
Data Visualisation with Matplotlib | Data Analytics #13
12 minLesson 14
Beautiful Charts with Seaborn in Python | Data Analytics #14
15 minLesson 15
Build a Streamlit Dashboard in Python | Data Analytics #15
12 minLesson 16
SQL Fundamentals for Data Analysts | Data Analytics #16
12 minLesson 17
SQL Joins & Aggregations Explained | Data Analytics #17
12 minLesson 18
Python + SQL: Real Analyst Queries | Data Analytics #18
12 minLesson 19
Automate Excel with Python | Data Analytics #19
12 minLesson 20
Excel Pivot Tables & Charts for Reporting | Data Analytics #20
10 minLesson 21
Pull Data from APIs with Python | Data Analytics #21
10 minLesson 22
Web Scraping with Python: Step by Step | Data Analytics #22
10 minLesson 23
Statistics Fundamentals Every Analyst Needs | Data Analytics #23
10 minLesson 24
Correlation, P-Values & Confidence Intervals | Data Analytics #24
10 minLesson 25
Machine Learning for Beginners in Python | Data Analytics #25
11 minLesson 26
Feature Engineering & Model Evaluation | Data Analytics #26
12 minLesson 27
Storytelling with Data: Present Like a Pro | Data Analytics #27
13 minLesson 28
Retail Analytics Deep Dive Project | Data Analytics #28
12 minLesson 29
Business Operations Analytics Deep Dive | Data Analytics #29
15 minLesson 30
End-to-End Analytics Capstone Project | Data Analytics #30
18 minLesson 1
Analyse E-Commerce Orders with Python Pandas | Full Project Tutorial
18 minLesson 2
Track Fitness & Health Data with Python Pandas | Hands-On Project
19 minLesson 3
HR Analytics with Pandas: Turnover & Retention Metrics in Python
17 minLesson 4
Build a Personal Finance Budget Tracker in Python with Pandas
18 minLesson 5
Real Estate Data Analysis with Pandas: Clean, Explore, Visualise
16 minLesson 6
Restaurant Reviews & Ratings Analysis with Python Pandas
21 minLesson 7
Retail Sales Analysis with Pandas: Find Trends & KPIs in Python
19 minLesson 8
Sports Analytics with Python Pandas: Player & Team Stats
57 minLesson 1
Pandas Zero to Hero: The Complete Beginner-to-Advanced Course
1 h 3 minLesson 2
Python Zero to Hero: The Complete Beginner-to-Advanced Course
33 minLesson 3
NumPy Zero to Hero: The Complete Beginner-to-Advanced Course
1 h 1 minLesson 4
Python for Beginners: From Variables to Real Mini Projects
34 minLesson 5
Time Series Analysis with Pandas
32 minLesson 6
End-to-End Data Analyst Capstone
27 minLesson 7
Web APIs & Requests In Depth
36 minLesson 8
Excel Automation with openpyxl
46 minLesson 1
Data Visualization for Beginners, with Matplotlib
35 minLesson 1
Python for Beginners: A Practical Introduction
1 h 30 minLesson 1
Pandas for Absolute Beginners (with Real Data)
45 minLesson 2
Data Visualization for Beginners, with Seaborn
1 h 15 minLesson 2
Python Full Tutorial for Beginners
1 h 4 minLesson 3
Learn Python: A Full Course for Beginners
53 minLesson 4
Python Full Course for Beginners
30 minLesson 1
Python Integers Explained: Bases, Division & Modulo | Data Types #1
27 minLesson 2
Python Floats Explained: Precision, Rounding & Pitfalls | Data Types #2
20 minLesson 3
Python Complex Numbers Explained: Real & Imaginary | Data Types #3
23 minLesson 4
Python Booleans & None Explained: Truthy vs Falsy | Data Types #4
35 minLesson 5
Python Strings Explained: Slicing, Methods & f-Strings | Data Types #5
21 minLesson 6
Python Lists Explained: Methods, Slicing & Comprehensions | Data Types #6
20 minLesson 7
Python Tuples Explained: Immutable, Fast & Unpackable | Data Types #7
21 minLesson 8
Python Dictionaries Explained: Keys, Methods & Nesting | Data Types #8
18 minLesson 9
Python Sets Explained: Union, Intersection & Difference | Data Types #9
14 minLesson 10
Python Frozensets Explained: Immutable Sets in Practice | Data Types #10
28 minLesson 11
Python Bytes Explained: Binary Data, Encoding & Decoding | Data Types #11
24 minLesson 12
Python Bytearrays Explained: Mutable Binary Data | Data Types #12
20 minLesson 1
Python os & sys Explained: Files, Env Vars & Args | Standard Library #1
20 minLesson 2
Python pathlib Explained: Modern File Paths Made Easy | Standard Library #2
20 minLesson 3
Python datetime Explained: Dates, Times & Time Zones | Standard Library #3
17 minLesson 4
Python collections Explained: Counter, deque & defaultdict | Standard Library #4
14 minLesson 5
Python itertools Explained: Iterators, Combinations & More | Standard Library #5
18 minLesson 6
Python functools Explained: lru_cache, partial & wraps | Standard Library #6
18 minLesson 7
Python re Explained: Regular Expressions Made Simple | Standard Library #7
18 minLesson 8
Python json & csv Explained: Read and Write Data Files | Standard Library #8
20 minLesson 9
Python math, random & statistics Explained | Standard Library #9
16 minLesson 10
Python subprocess Explained: Run External Commands Safely | Standard Library #10
17 minLesson 12
Python asyncio Explained: async/await & Event Loops | Standard Library #12
15 minLesson 13
Python logging Explained: Loggers, Handlers & Formatters | Standard Library #13
16 minLesson 14
Python argparse Explained: Build Real CLI Tools | Standard Library #14
16 minLesson 15
Python pickle & shelve Explained: Save Objects to Disk | Standard Library #15
17 minLesson 16
Python hashlib, hmac & secrets Explained: Secure Your Code | Standard Library #16
17 minLesson 17
Python contextlib Explained: Custom Context Managers | Standard Library #17
18 minLesson 18
Python dataclasses Explained: Cleaner Classes, Less Code | Standard Library #18
18 minLesson 19
Python typing & enum Explained: Type Hints Done Right | Standard Library #19
18 minLesson 20
Python unittest Explained: Write Tests That Catch Bugs | Standard Library #20
17 minLesson 21
Python shutil, tempfile & glob Explained: File Operations | Standard Library #21
16 minLesson 22
Python io, string & textwrap Explained: Text & Streams | Standard Library #22
17 minLesson 23
Python uuid, base64 & binascii Explained: Encode Anything | Standard Library #23
18 minLesson 24
Python abc & inspect Explained: Abstract Classes & Introspection | Standard Library #24
18 minLesson 25
Build a Python CLI Tool from Scratch | Standard Library Capstone #25
17 minLesson 1
Probability Foundations for Data Analysts | Statistics #1
16 minLesson 2
Discrete Distributions Explained: Binomial & Poisson | Statistics #2
18 minLesson 3
Continuous Distributions & the Normal Curve | Statistics #3
14 minLesson 4
The Central Limit Theorem, Finally Explained | Statistics #4
16 minLesson 5
Sampling Methods & How Bias Sneaks In | Statistics #5
16 minLesson 6
Confidence Intervals Done Properly | Statistics #6
16 minLesson 7
Hypothesis Testing Fundamentals | Statistics #7
16 minLesson 8
A/B Testing & Experiment Design That Works | Statistics #8
12 minLesson 9
Non-Parametric Tests: When Assumptions Fail | Statistics #9
13 minLesson 10
Multiple Comparisons & P-Value Corrections | Statistics #10
13 minLesson 11
Simple Linear Regression Explained | Statistics #11
13 minLesson 12
Multiple Regression & Model Diagnostics | Statistics #12
15 minLesson 13
Categorical Data Analysis & Chi-Square Tests | Statistics #13
15 minLesson 14
Bayesian Statistics Basics for Analysts | Statistics #14
15 minLesson 15
Statistics Capstone: A Full Real-World Analysis | Statistics #15
25 minLesson 1
Linear Regression from Scratch in Python | ML Algorithms #1
21 minLesson 2
Logistic Regression for Classification | ML Algorithms #2
20 minLesson 3
K-Nearest Neighbours (KNN) Explained | ML Algorithms #3
17 minLesson 4
Decision Trees: How They Really Work | ML Algorithms #4
17 minLesson 5
Random Forests Explained with Python | ML Algorithms #5
17 minLesson 6
Gradient Boosting Explained Step by Step | ML Algorithms #6
17 minLesson 7
Support Vector Machines Made Intuitive | ML Algorithms #7
16 minLesson 8
Naive Bayes Classifier Explained | ML Algorithms #8
17 minLesson 1
Scikit-learn Tutorial #1: The Estimator API Explained
17 minLesson 2
Scikit-learn Tutorial #2: Preprocessing — Scalers
16 minLesson 3
Scikit-learn Tutorial #3: Preprocessing — Encoders
15 minLesson 4
Scikit-learn Tutorial #4: Handling Missing Data
16 minLesson 5
Scikit-learn Tutorial #5: Feature Engineering
15 minLesson 6
Scikit-learn Tutorial #6: Pipelines
15 minLesson 7
Scikit-learn Tutorial #7: ColumnTransformer
15 minLesson 8
Scikit-learn Tutorial #8: Splitting & Cross-Validation
15 minLesson 9
Scikit-learn Tutorial #9: Hyperparameter Tuning
15 minLesson 10
Scikit-learn Tutorial #10: Classification Metrics
14 minLesson 11
Scikit-learn Tutorial #11: Regression Metrics
14 minLesson 12
Scikit-learn Tutorial #12: Clustering Metrics
14 minLesson 13
Scikit-learn Tutorial #13: Feature Selection
14 minLesson 14
Scikit-learn Tutorial #14: Text Data & Vectorisation
14 minLesson 15
Scikit-learn Tutorial #15: Ensembling & Meta-Estimators
15 minLesson 16
Scikit-learn Tutorial #16: Custom Estimators
15 minLesson 17
Scikit-learn Tutorial #17: Model Persistence & Diagnostics
16 minLesson 18
Scikit-learn Tutorial #18: Capstone — End-to-End ML Pipeline
13 minLesson 1
FastAPI Tutorial #1: Getting Started — Build Your First Python API
14 minLesson 2
FastAPI Tutorial #2: Path & Query Parameters Explained
15 minLesson 3
FastAPI Tutorial #3: Request Bodies & Pydantic Models
16 minLesson 4
FastAPI Tutorial #4: Response Models & HTTP Status Codes
17 minLesson 5
FastAPI Tutorial #5: Data Validation with Pydantic
17 minLesson 6
FastAPI Tutorial #6: Path Operation Configuration & Better Docs
17 minLesson 7
FastAPI Tutorial #7: Dependency Injection with Depends()
17 minLesson 8
FastAPI Tutorial #8: Class-Based & Sub-Dependencies
21 minLesson 1
Introduction to Market Research and Analytics in Python
20 minLesson 2
Primary vs Secondary Market Research Data Explained for Analytics Training
20 minLesson 3
Quantitative vs Qualitative Research Methods: Key Differences for Market Analysts
22 minLesson 4
Market Research Workflow Using Python: Step-by-Step Training Guide
23 minLesson 5
Setting Up Python and Jupyter for Market Research Analytics
22 minLesson 6
Python Basics for Market Research Analysis: Essential Training
24 minLesson 7
Working with Lists, Dictionaries, and Functions in Python for Market Research Analytics
23 minLesson 8
Numerical Analysis with NumPy for Market Data Training
21 minLesson 9
Introduction to Pandas for Market Research: Master Data Analysis with Python
25 minLesson 10
How to Load Survey and Market Data from CSV & Excel in Python | Market Research Analytics
19 minLesson 11
Mastering Survey & Market Research Dataset Structures in Python | Analytics Training
17 minLesson 12
Understanding Demographic Variables in Market Research Analytics with Python
21 minLesson 13
Likert Scale and Rating Question Analysis in Python for Market Research
20 minLesson 14
Handling Open-Ended Survey Responses in Python for Market Research
23 minLesson 15
Assessing Data Quality in Market Research
20 minLesson 16
How to Identify Missing and Invalid Survey Responses in Python | Market Research Analytics
32 minLesson 17
Cleaning and Standardizing Market Research Data Using Python: Step-by-Step Tutorial
21 minLesson 18
Removing Duplicate and Biased Responses in Market Research Analytics with Python
18 minLesson 19
Encoding Categorical and Survey Variables in Python | Market Research Analytics Tutorial
26 minLesson 20
How to Prepare Clean, Analysis-Ready Datasets for Market Research Using Python
26 minLesson 21
Descriptive Statistics for Market Research Using Python | Comprehensive Analysis Guide
19 minLesson 22
Master Frequency Tables & Percentage Analysis for Market Research Using Python
28 minLesson 23
Cross Tabulation and Segment Comparisons in Python for Market Research Analysis
25 minLesson 24
Visualizing Survey and Market Data Using Python for Market Research
23 minLesson 25
Interpreting Patterns and Market Trends in Python Market Research Analytics
20 minLesson 26
Introduction to Market Segmentation: Essential Concepts for Market Research Analytics in Python
21 minLesson 27
Demographic Segmentation Analysis for Market Research in Python
21 minLesson 28
Behavioral and Attitudinal Segmentation in Market Research
19 minLesson 29
Rule Based Customer Segmentation in Python: Step-by-Step Training
21 minLesson 30
Customer Clustering Using K-Means
26 minLesson 31
Statistical Thinking for Market Insights: Training for Data-Driven Decision Making
25 minLesson 32
Hypothesis Testing in Market Research: Essential Methods and Practical Python Analysis
22 minLesson 33
Comparing Groups Using t-Tests: A Practical Guide for Market Research Analytics in Python
25 minLesson 34
Chi-Square Tests for Analyzing Survey Relationships Using Python | Market Research Analytics
28 minLesson 35
Correlation and Key Driver Analysis in Market Research
25 minLesson 37
Measuring Customer Satisfaction with Market Research Data
20 minLesson 38
Net Promoter Score Analysis in Python for Market Research
27 minLesson 39
Master Brand Awareness & Perception Metrics Using Python for Market Research
23 minLesson 41
Cleaning Open-Ended Survey Text Data for Market Research in Python
24 minLesson 42
Master Word Frequency & Keyword Analysis for Market Research Using Python
19 minLesson 43
Basic Sentiment Analysis for Survey Feedback Using Python
26 minLesson 44
Identifying Common Themes in Customer Comments with Python Analytics
22 minLesson 45
Visualizing Text-Based Market Insights in Python for Market Research
21 minLesson 46
Introduction to Trend Analysis in Market Research
27 minLesson 47
Analyzing Market and Consumer Trends Over Time Using Python | Market Research Analytics
21 minLesson 48
Customer Cohort Analysis Training in Python for Market Research
24 minLesson 49
Retention and Churn Analysis Using Python for Market Research
27 minLesson 50
Introductory Market Trend Forecasting
18 minLesson 51
Turning Market Analysis into Business Insights with Python
23 minLesson 52
Writing Insight-Driven Market Research Summaries in Python
24 minLesson 53
Data Storytelling for Stakeholders: Enhance Market Research Analytics Skills
27 minLesson 54
Best Practices for Market Research Visuals | Python Analytics Tutorial
15 minLesson 55
Exporting Analysis Results and Reports in Python for Market Research
24 minLesson 56
End-to-End Market Research Analytics Project
21 minLesson 57
Customer Segmentation Case Study Using Python for Market Research Analytics
23 minLesson 58
Market Insights and Recommendations Case Study with Python Analytics
24 minLesson 1
Introduction to Pandas: Essential Tools for Data Analysis in Python
24 minLesson 2
Installing Pandas and Setting Up Your Python Environment for Data Science Success
12 minLesson 3
Understanding Pandas Series and DataFrames: Essential Python Data Structures for Analysis
13 minLesson 4
Mastering DataFrames in Python Pandas: Creating & Inspecting for Data Science
28 minLesson 6
Introduction to Pandas DataFrame: Essential Operations and Attributes Explained
17 minLesson 7
How to Import and Export Data in Pandas: CSV, Excel, JSON, and SQL Explained
19 minLesson 8
Exploring and Cleaning Real-World Datasets with Python Pandas: A Practical Guide
22 minLesson 9
Hands-On With Pandas: Creating and Exploring DataFrames
13 minLesson 10
Introduction to Data Analysis with the Titanic Dataset Using Pandas
24 minLesson 11
How to Identify and Handle Missing Data in Python Pandas for Accurate Data Analysis
17 minLesson 13
How to Rename Columns and Indexes in pandas DataFrames for Clear Data Analysis
21 minLesson 14
How to Change Data Types and Convert Units in Pandas for Accurate Data Analysis
14 minLesson 15
Comprehensive Guide to String Operations and Text Cleaning with Pandas in Python
19 minLesson 17
Effective Techniques for Handling Outliers and Validating Data in Pandas
17 minLesson 19
Mastering Conditional Selection & Boolean Indexing in Pandas for Data Analysis
17 minLesson 20
Master Filtering Rows and Columns in Pandas Using Query and isin for Data Analysis
18 minLesson 21
Mastering Data Sorting and Ranking Techniques with Pandas in Python
12 minLesson 23
Mastering Pandas DataFrames: Applying Functions Across Rows & Columns for Data Analysis
20 minLesson 24
Master Lambda Functions & Vectorized Operations in Pandas for Faster Data Analysis
15 minLesson 26
How to Concatenate DataFrames Vertically and Horizontally Using Pandas in Python
36 minLesson 27
Mastering DataFrame Merges in Pandas: Inner, Outer, Left & Right Joins Explained
14 minLesson 29
Master Grouping and Aggregation in Python for Effective Data Analysis
21 minLesson 30
Understanding Multi-Level Grouping and Custom Aggregations in Pandas for Data Analysis
15 minLesson 31
Master Pivot Tables & Cross-Tabulations in Python Pandas for Powerful Data Analysis
17 minLesson 32
Mastering Data Reshaping in Pandas with Melt, Stack, and Unstack Functions
12 minLesson 34
Mastering Dates and Times in Pandas for Effective Data Analysis
16 minLesson 35
Converting Strings to Datetime and Extracting Date Components Using Pandas in Python
15 minLesson 36
Mastering Time Series Analysis in Python: Resampling, Shifting, and Rolling Windows with Pandas
20 minLesson 38
Mastering Time-Based Grouping and Aggregations in Pandas for Effective Data Analysis
20 minLesson 41
Master Pandas Series: Advanced Slicing & Cross-Section Techniques for Data Analysis
21 minLesson 44
Efficient Data Analysis with Pandas: Master Method Chaining & Pipelines in Python
18 minLesson 45
Optimizing Large Datasets in Pandas: Efficient Techniques for Data Processing
17 minLesson 46
Quick and Effective Data Visualization with Pandas plot() in Python
25 minLesson 47
How to Use Pandas with Matplotlib and Seaborn for Effective Data Visualization
17 minLesson 48
How to Create Line, Bar, Histogram, and Box Plots Using Python and Pandas
15 minLesson 49
Understanding Data Correlation and Heatmap Visualization Using Python and Pandas
17 minLesson 50
Turn Raw Data into Interactive Charts (Plotly + Pandas)
27 minLesson 51
Step-by-Step Guide to Exploratory Data Analysis (EDA) Using Python and Pandas
21 minLesson 52
Master Feature Engineering with Pandas for Powerful Data Preprocessing
19 minLesson 53
Essential Data Preparation Techniques for Effective scikit-learn Machine Learning Models
16 minLesson 54
How to Encode Categorical Variables in Pandas for Effective Data Preparation
21 minLesson 58
How to Create an Interactive KPI Dashboard Using Python and Pandas
21 minLesson 59
Volatility and Risk Analysis Training for Finance and Stock Market
36 minLesson 69
Comprehensive Pandas Tutorial in Python: Data Analysis from Beginner to Advanced
24 minLesson 1
Introduction to Retail and E-commerce Analytics with Python
23 minLesson 2
Understanding Retail Business Models for E-commerce and Analytics
26 minLesson 3
Understanding Types of Retail and E-commerce Data for Effective Python Analytics
19 minLesson 4
Retail Analytics Workflow Using Python: Step-by-Step Training for E-commerce Data
24 minLesson 8
Numerical Analysis with NumPy for Retail Data Training
21 minLesson 9
Introduction to Pandas for Retail Analytics Using Python
23 minLesson 10
Loading Retail Transaction Data from CSV and Excel in Python
19 minLesson 11
Structure of Retail Transaction Datasets for Data Analytics Training
23 minLesson 12
Understanding Product and Category Data for Retail E-commerce Analytics
23 minLesson 13
Customer and Order Data in Retail Systems: Python Training for E-commerce Analytics
21 minLesson 14
Pricing, Discounts, and Revenue Fields in Python for E-commerce Analytics Training
27 minLesson 15
Assessing Retail Data Quality in Python for E-commerce Analytics | Step-by-Step Guide
20 minLesson 16
How to Identify Missing and Invalid Retail Records Using Python for E-commerce Analytics
24 minLesson 17
Master Cleaning and Standardizing Product Data for Retail E-commerce Analytics
22 minLesson 18
Effective Techniques to Handle Duplicate Orders in Python for Retail E-commerce Analytics
26 minLesson 19
Encoding Categorical Retail Variables for Machine Learning in Python
20 minLesson 21
Descriptive Statistics for Retail Data Analysis in Python
20 minLesson 22
Analyzing Sales by Product and Category in Python for Retail E-commerce
27 minLesson 23
Customer Purchase Behavior Analysis Training with Python for Retail E-commerce Analytics
24 minLesson 24
Visualizing Retail Sales Data with Python for E-commerce Analytics
24 minLesson 25
Master Interpreting Retail Performance Patterns Using Python for E-commerce Analytics
22 minLesson 26
Introduction to Customer Analytics for Retail and E-commerce
21 minLesson 30
Customer Clustering Using K-Means in Python for Retail Analytics
24 minLesson 31
Product Performance Analysis with Python for Retail E-commerce Analytics
20 minLesson 32
Top Selling and Low-Performing Products Analysis with Python for Retail E-commerce
23 minLesson 35
Product Bundle Insights and Cross-Selling Strategies with Python for Retail Analytics
21 minLesson 37
Master Average Order Value & Conversion Metrics with Python for Retail E-commerce
23 minLesson 38
Channel and Regional Sales Analysis Using Python for Retail E-commerce Insights
24 minLesson 40
Unlock Revenue Growth Opportunities in Retail E-Commerce with Python Analytics
27 minLesson 41
Introduction to Machine Learning in Retail: Practical Training for E-commerce Analytics
20 minLesson 43
Product Recommendation Systems Training for E-commerce Analytics with Python
16 minLesson 44
Predicting Customer Churn in Retail Using Python Analytics
23 minLesson 45
Demand Prediction Using Machine Learning for Retail E-Commerce Analytics
21 minLesson 46
Introduction to Retail Sales Forecasting with Python for E-commerce Analytics
25 minLesson 48
Seasonal Demand Forecasting Training with Python for Retail E-commerce Analytics
25 minLesson 50
Evaluating Forecast Accuracy: Techniques for Retail E-commerce Analytics in Python
24 minLesson 51
Turning Retail Data into Business Insights with Python Analytics
23 minLesson 52
Designing Retail Analytics Dashboards with Python for E-commerce Insights
21 minLesson 53
Data Storytelling for Retail Decision Makers: Practical Training for Impactful Insights
20 minLesson 55
Exporting Retail Analysis Reports Using Python for E-commerce Analytics
23 minLesson 56
End to End Retail Analytics Project Training with Python for E-commerce
19 minLesson 57
Customer Segmentation Case Study: Python Training for Retail E-commerce Analytics
18 minLesson 58
Retail Sales Forecasting Case Study Training with Python for E-commerce Analytics
28 minLesson 1
Introduction to Social Media and Content Analytics
20 minLesson 2
Understanding Social Media Platforms and Metrics
25 minLesson 3
Types of Social Media Data: Views, Likes, CTR, and Watch Time
24 minLesson 4
Social Media Analytics Workflow Using Python
30 minLesson 5
Setting Up Python and Jupyter for Social Media Analytics
29 minLesson 6
Python Basics for Social Media Data Analysis
25 minLesson 7
Working with Lists, Dictionaries, and Functions for Social Media Content Analytics
21 minLesson 8
Numerical Analysis with NumPy for Engagement Data
31 minLesson 10
Loading Social Media Data from CSV and APIs
30 minLesson 12
Understanding Video Metadata: Title, Tags, Category
30 minLesson 14
Watch Time and Retention Data Explained
26 minLesson 16
Identifying Missing and Inconsistent Social Media Data
23 minLesson 18
Handling Duplicate Content Records in Social Media Analytics
26 minLesson 19
Encoding Categorical Variables in Social Media Data
27 minLesson 22
Analyzing Views and Watch Time Distribution
25 minLesson 23
Engagement Rate Analysis: Likes, Comments, Shares
24 minLesson 24
Visualizing Content Performance
23 minLesson 25
Interpreting Content Trends and Patterns
28 minLesson 26
Introduction to Audience Analytics
29 minLesson 27
Analyzing Audience Behavior and Engagement Patterns
24 minLesson 30
Sentiment Analysis on Social Media Comments
31 minLesson 31
Identifying Top-Performing Content in Social Media Analytics
24 minLesson 34
Analyzing Content Categories and Niches
23 minLesson 35
Detecting High-Impact Content Features
25 minLesson 36
Understanding Click-Through Rate (CTR) in Social Media and Content Analytics
27 minLesson 37
Thumbnail and Title Performance Analysis
29 minLesson 40
Designing Data-Driven Content Strategies
29 minLesson 41
Introduction to Social Media APIs
26 minLesson 42
Extracting Data Using the YouTube Data API
29 minLesson 44
Scheduling Data Updates with Python
32 minLesson 45
Building Automated Content Analytics Systems
29 minLesson 47
Analyzing Growth in Views and Subscribers
31 minLesson 48
Detecting Viral Spikes and Trends in Social Media Data
30 minLesson 51
Introduction to Machine Learning for Social Media
21 minLesson 54
Feature Importance for Engagement Prediction
32 minLesson 56
Turning Social Media Data into Insights
26 minLesson 57
Designing Content Analytics Dashboards
31 minLesson 58
Data Storytelling for Content Creators
29 minLesson 59
Best Practices for Visualizing Engagement Data
28 minLesson 61
End-to-End YouTube Analytics Project
24 minLesson 62
Viral Video Detection: A Social Media Case Study
15 minLesson 1
1 - Capstone Project in Python
15 minLesson 2
2 - Git and GitHub Basics for Python Projects
11 minLesson 3
Mastering Virtual Environments in Python for Effective Data Science Projects
9 minLesson 4
4 - Writing Clean Code with PEP 8 in Python
13 minLesson 5
5 - Automating Repetitive Tasks in Python
11 minLesson 6
6 - APIs and Web Scraping in Python
20 minLesson 7
Python and Jupyter Notebooks for Beginners: A Step-by-Step Guide
11 minLesson 10
Master Python Strings: Essential Operations and Methods for Data Science
11 minLesson 24
02 NumPy Indexing: Learn Array Access and Manipulation in Python
12 minLesson 25
Master NumPy Math Operations: Essential Python Techniques for Data Science
15 minLesson 27
Mastering Pandas DataFrames: Essential Techniques for Data Science in Python
13 minLesson 28
06 Reading CSV, Excel, and JSON Files in Python
13 minLesson 29
07 Writing CSV, Excel, and JSON Files in Python
12 minLesson 30
Master Selecting and Filtering Data in Python for Data Science
14 minLesson 31
Date and Time Basics in Python: Essential Skills for Data Science Beginners
16 minLesson 32
10 - Sales Data Analysis in Python: Step-by-Step Tutorial
13 minLesson 33
1 Handling Missing Values in Python for Data Cleaning
15 minLesson 34
How to Clean and Remove Duplicate Data in Python Using Pandas
10 minLesson 35
3 - String Cleaning and Data Type Conversion in Python
14 minLesson 37
5 - Feature Engineering Basics in Python
12 minLesson 38
Mastering DataFrame Merging in Python: Essential Techniques for Data Preparation
11 minLesson 40
8 - Movie Dataset Cleanup in Python: Data Preparation Techniques
15 minLesson 41
1 - Matplotlib- Line, Bar, Scatter, Histogram
12 minLesson 42
2 - Seaborn- Countplot, Boxplot, Heatmap
13 minLesson 43
Master Styling, Annotations & Saving Techniques for Python Data Visualization
12 minLesson 44
4 - Building a Weather Trends Dashboard in Python with Data Visualization
9 minLesson 45
1 - Inspecting Data in Python: Essential Techniques for EDA
16 minLesson 46
Distribution & Relationship Analysis in Python | Exploratory Data Analysis Tutorial
10 minLesson 51
1 Descriptive Statistics in Python for Data Science
1 minLesson 52
2 Probability and Normal Distribution in Python
14 minLesson 53
3 Sampling and Confidence Intervals in Python
12 minLesson 54
4 Hypothesis Testing in Python: Step-by-Step Guide for Data Science
13 minLesson 55
5 - Survey Analysis in Python: Statistical Techniques for Data Science
17 minLesson 56
1 - Supervised vs Unsupervised Learning in Python
15 minLesson 57
2 - Train-Test Split in Python
14 minLesson 58
3 - Regression and Classification in Python
13 minLesson 60
5 - Feature Scaling in Python
11 minLesson 61
Understanding Decision Trees and Random Forests in Python for Classification
25 minLesson 2
Setting Up Python Jupyter Notebooks for Probability and Statistics Analysis
7 minLesson 3
Understanding Data Types: Categorical, Numerical, Continuous, and Discrete Explained
10 minLesson 4
Master Descriptive Statistics: Learn Mean, Median, and Mode in Python
15 minLesson 5
Measures of Spread Explained: Variance, Standard Deviation & Interquartile Range
14 minLesson 6
Fundamentals of Data Visualization: Histograms, Boxplots, and Scatterplots Explained
11 minLesson 7
Foundations of Probability: Understanding Events, Outcomes, and Sample Space
11 minLesson 8
Understanding Conditional Probability and Independence in Probability Theory
24 minLesson 9
Master Bayes Theorem: Real-Life Examples & Step-by-Step Probability Explained
9 minLesson 10
Understanding Bernoulli, Binomial, and Poisson Discrete Probability Distributions
14 minLesson 11
Understanding Continuous Probability Distributions: Uniform, Normal, and Exponential Explained
13 minLesson 12
Understanding Statistical Sampling and the Law of Large Numbers in Biblical Context
14 minLesson 13
Understanding the Central Limit Theorem: Key Concepts and Practical Applications
12 minLesson 15
Hypothesis Testing Explained: Concepts, Errors, and How to Interpret P-Values in Python
11 minLesson 16
Understanding t-Tests, Chi-Square Tests, and ANOVA in Python for Statistical Analysis
16 minLesson 17
Understanding Bootstrapping for Estimation and Confidence Intervals in Statistics
12 minLesson 18
Understanding Permutation Tests: A Flexible Approach to Hypothesis Testing
17 minLesson 19
Understanding Monte Carlo Simulations in Python for Statistical Modeling and Analysis
21 minLesson 20
Mastering Random Number Generation in Python Using NumPy: Techniques & Applications
29 minLesson 21
Practical Applications of Simulation Techniques in Statistical Analysis and Decision-Making
13 minLesson 22
Understanding Covariance and Correlation: Pearson and Spearman Explained
12 minLesson 23
Simple Linear Regression in Python: Model Fitting & Interpretation Guide
11 minLesson 24
Understanding Multiple Linear Regression with Python’s Statsmodels Library
12 minLesson 25
Understanding Regression Diagnostics: Residuals and Key Assumptions Explained
10 minLesson 26
Practical Regression Project: Predicting Housing Prices with Python and Data Analysis
12 minLesson 28
Logistic Regression Explained: Master Coefficients & Odds Ratios Easily
14 minLesson 29
Master Accuracy, Precision & Recall for Evaluating Classification Models in Python
12 minLesson 30
Understanding ROC Curves and AUC for Evaluating Classification Models in Python
24 minLesson 33
Understanding Stationarity, ACF, PACF, and ARIMA Fundamentals in Time Series Analysis
24 minLesson 34
Understanding Bayesian Statistics: Foundations of Priors and Posteriors Explained
15 minLesson 35
Bayesian Estimation Explained: Using SciPy and PyMC for Practical Inference in Python
21 minLesson 36
Practical Applications of Bayesian Inference: Step-by-Step Examples and Analysis
16 minLesson 37
Understanding the Law of Large Numbers Through Dice Roll Simulations in Python
19 minLesson 38
Hypothesis Testing Explained: Applying Statistical Methods to Real-World Data
12 minLesson 40
Comprehensive Time Series Forecasting Project: From Data Preparation to Deployment
34 minLesson 41
Comprehensive Statistical Analysis: Step-by-Step Capstone Project Case Study
12 minLesson 3
How to Set Up Python and Jupyter Notebook for Data Visualization Beginners
11 minLesson 4
Understanding NumPy Arrays and Random Data Generation for Data Analysis in Python
14 minLesson 6
Master Data Cleaning and Preparation with Pandas in Python for Effective Bible Study Analysis
14 minLesson 8
Introduction to Matplotlib: Creating and Customizing Line and Bar Plots in Python
15 minLesson 9
How to Create and Customize Scatter Plots and Histograms in Matplotlib
12 minLesson 10
How to Customize Titles, Labels, and Legends in Matplotlib for Clearer Data Visualization
14 minLesson 11
Mastering Subplots and Multiple Axes in Matplotlib for Effective Data Visualization
15 minLesson 12
Enhancing Matplotlib Plots: Mastering Colors, Markers, and Line Styles in Python
15 minLesson 13
How to Save and Export High-Quality Matplotlib Plots for Publication and Presentation
10 minLesson 14
Introduction to Seaborn for Data Visualization with Built-in Python Datasets
11 minLesson 15
Understanding Distribution Plots in Python: Histogram, KDE, Violin, and Box Plots Explained
11 minLesson 16
Visualizing Categorical Data in Python with Seaborn: Bar, Count, and Swarm Plots
14 minLesson 17
Understanding Relationship Plots in Seaborn: Scatter, Regression, and Pairplot Explained
13 minLesson 18
Understanding Heatmaps and Correlation Matrices with Seaborn for Data Analysis
10 minLesson 19
Mastering Custom Themes and Aesthetics in Seaborn for Clear Data Visualization
14 minLesson 20
How to Use Annotations and Highlights to Enhance Data Visualization in Plots
12 minLesson 21
Master Customizing Axes in Python: Ticks, Scales & Logarithmic Transformations
11 minLesson 22
Creating Interactive Dashboards by Combining Multiple Plots for Effective Data Visualization
12 minLesson 23
Best Practices for Data Storytelling Using Visuals in Bible Teaching | Week 07–08
10 minLesson 24
Introduction to Plotly: Creating Interactive Charts with Python
11 minLesson 25
Creating Interactive Scatter, Line, and Bar Charts with Plotly in Python
14 minLesson 27
Interactive Data Filtering in Bokeh: Building Dynamic Visualizations with Python
10 minLesson 29
Introduction to GeoPandas: Working with Shapefiles and Geospatial Maps in Python
13 minLesson 30
Creating Interactive Choropleth Maps with Plotly for Python Geospatial Visualization
14 minLesson 31
3 - Interactive Maps with Folium
14 minLesson 32
Geospatial Analysis Case Study: Mapping and Visualizing Real-World Location Data
15 minLesson 36
4 - Advanced Dash - Layouts, Callbacks, Hosting
10 minLesson 37
Visualizing Network Graphs with NetworkX and PyVis in Python
14 minLesson 38
Time Series Visualization Techniques Using Matplotlib and Plotly in Python
14 minLesson 40
Creating 3D and Animated Data Visualizations in Python with Matplotlib and Plotly
11 minLesson 41
Master Visual Design Principles for Effective Communication in Python Data Visualization
10 minLesson 42
2 - Case Study Project - Sales and Marketing Dashboard
9 minLesson 43
Climate Data Analysis & Geospatial Visualization: Expert Case Study Techniques
13 minLesson 44
Build an Interactive Data Visualization App: Capstone Project Step-by-Step Guide
19 minLesson 2
How to Scrape and Analyze Movie Reviews Using Python and Data Science Techniques
16 minLesson 3
Biblical Principles in Data Analysis: Scraping and Analyzing Product Prices with Python
19 minLesson 4
Building a News Data Scraping and Analysis Project Using Python
16 minLesson 5
Web Scraping and Visualization Techniques for Real Estate Data Analysis
14 minLesson 6
How to Extract YouTube Channel Video Data Using Python and YouTube Data API
21 minLesson 10
Comprehensive Airbnb Data Analysis Using Python for Biblical Stewardship Insights
18 minLesson 11
Comprehensive Analysis and Visualization of Global Covid-19 Data Using Python
22 minLesson 15
Analyzing and Predicting Iris Flower Species Using Data Science Techniques
23 minLesson 17
Building a Car Price Prediction Model Using Python and Data Science Techniques
20 minLesson 20
Analyzing Uber Trips Data: A Step-by-Step Guide to Data Science Techniques
18 minLesson 26
Predicting Wine Quality with Machine Learning: A Step-by-Step Guide Using Python
25 minLesson 27
Building Accurate Disease Prediction Models with Machine Learning: A Step-by-Step Guide
23 minLesson 29
Predicting Heart Disease with Logistic Regression: A Step-by-Step Python Guide
15 minLesson 30
Building a House Price Prediction Model with Python: Data Science and Machine Learning
17 minLesson 31
Applying Linear Regression to the Boston Housing Dataset: A Step-by-Step Guide
24 minLesson 33
Classifying Cancer Cells with Scikit-learn: A Step-by-Step Guide for Beginners
24 minLesson 35
Predicting Box Office Revenue with Linear Regression: A Step-by-Step Guide
27 minLesson 36
Online Payment Fraud Detection Using Machine Learning in Python | Data Science Project
24 minLesson 38
Building and Training Handwritten Digit Recognition Models with Scikit Learn
26 minLesson 40
Building a Credit Card Fraud Detection System with Machine Learning Techniques
20 minLesson 41
Building a Recommendation System in Python: A Step-by-Step Guide for Beginners
21 minLesson 44
Anomaly Detection in Time Series Data: Techniques and Practical Applications
23 minLesson 49
Deep Learning for Wine Type Classification: Step-by-Step Model Training Guide
22 minLesson 51
Building a Neural Network for Handwritten Digit Recognition: A Step-by-Step Guide
24 minLesson 53
Logistic Regression for Handwritten Digit Recognition Using PyTorch: Step-by-Step Tutorial
17 minLesson 56
How to Count Objects in Images Using Python and OpenCV: A Step-by-Step Guide
15 minLesson 68
Building an Interactive Retail Sales Dashboard with Plotly and Streamlit in Python
20 minLesson 69
Building a COVID-19 Data Tracker with API Integration and Time-Series Visualization in Python
17 minLesson 73
Customer Churn Prediction: Step-by-Step Classification Models in Python
13 minLesson 76
4 - Loan Default Prediction - Risk Modeling
19 minLesson 77
Predicting House Prices with Regression Using the Ames Housing Dataset
17 minLesson 79
Applying Binary Classification for Accurate Diabetes Prediction in Healthcare
15 minLesson 83
Detecting Fake News with NLP and Transformer Models: A Biblical Perspective
22 minLesson 1
Understanding Data Mining and the Knowledge Discovery in Databases (KDD) Process
22 minLesson 2
Data Mining vs Data Science vs Machine Learning: Key Differences Explained
26 minLesson 4
Introduction to Python, Pandas, and scikit-learn for Data Analysis and Machine Learning
13 minLesson 5
Fundamentals of Exploratory Data Analysis and Visualization for Biblical Data Insights
17 minLesson 6
Data Cleaning Fundamentals: Managing Missing Values, Noise, and Outliers in Datasets
20 minLesson 7
Understanding Data Transformation: Normalization, Encoding, and Feature Scaling in Machine Learning
22 minLesson 8
Understanding Principal Component Analysis (PCA) for Dimensionality Reduction in Data
13 minLesson 10
Essential Data Preprocessing Techniques Using Titanic and Iris Datasets in Python
25 minLesson 11
Foundations of Exploratory Data Mining in Descriptive Analytics
16 minLesson 12
Understanding Summarization and Descriptive Statistics in Data Mining
16 minLesson 13
Understanding Histograms, Scatterplots, and Heatmaps for Data Visualization
17 minLesson 14
Understanding Association Rule Mining with the Apriori Algorithm: A Step-by-Step Guide
26 minLesson 16
Understanding Decision Trees: ID3, C4.5, and CART Algorithms for Classification
29 minLesson 17
Mastering Naive Bayes Classifier: Key Concepts and Real-World Data Analysis Applications
15 minLesson 19
Master Logistic Regression for Binary Classification: Step-by-Step Practical Guide
20 minLesson 20
Understanding Classifier Evaluation: Accuracy, Precision, Recall, and F1-Score Explained
19 minLesson 21
Understanding ROC Curves, AUC, and Confusion Matrix for Classification Model Evaluation
23 minLesson 22
Customer Churn Prediction: Step-by-Step Python Tutorial Using Real Data
16 minLesson 24
Understanding the k-Means Clustering Algorithm: A Clear Step-by-Step Guide
21 minLesson 26
Understanding Density-Based Clustering with DBSCAN: Principles and Python Implementation
15 minLesson 27
Understanding 5 Key Cluster Evaluation Metrics for Effective Machine Learning Analysis
16 minLesson 28
Understanding Socio-Economic Segmentation Through Hands-On Clustering Techniques
22 minLesson 29
Predicting Diabetes Using Ensemble Machine Learning Models: A Step-by-Step Guide
23 minLesson 30
Understanding Bagging and Random Forests: Ensemble Methods in Machine Learning
17 minLesson 31
Understanding AdaBoost and XGBoost: Key Boosting Techniques in Machine Learning
23 minLesson 32
Support Vector Machines (SVM): Principles, Methods, and Practical Applications
19 minLesson 35
Foundations of Anomaly and Outlier Detection in Data Analysis Explained
19 minLesson 36
Understanding Statistical Outlier Detection: Methods and Practical Applications in Python
12 minLesson 38
ARIMA Modeling in Python: Classical Forecasting Techniques Explained
21 minLesson 44
Sentiment Analysis with Text Mining: A Practical Data Science Capstone Project
26 minLesson 45
Comprehensive Data Mining Capstone Project: Step-by-Step Case Study Walkthrough
11 minLesson 1
01 Introduction to Python in Jupyter Notebook
28 minLesson 3
Master Python Data Structures: Lists, Tuples, Sets & Dictionaries Explained Clearly
24 minLesson 5
Comprehensive Guide to Pandas Series and DataFrames for Data Analysis in Python
11 minLesson 6
How to Import and Export CSV, Excel, and JSON Files in Python for Data Management
10 minLesson 9
Understanding Probability Distributions in Python with SciPy for Statistical Analysis
14 minLesson 10
Understanding Correlation and Covariance in Python for Statistical Analysis
34 minLesson 12
Data Visualization with Matplotlib
12 minLesson 13
Mastering Resampling and Aggregation of Time Series Data with Pandas in Python
16 minLesson 14
Master Rolling Mean & Exponential Moving Average in Python for Time Series Analysis
16 minLesson 15
Foundations of Time Series Analysis: Understanding Trend and Seasonality in Data
19 minLesson 16
Understanding Trend, Seasonality, Cyclicity, and Noise in Time Series Analysis
12 minLesson 17
Resampling & Aggregation in Pandas: Master Time Series Data Analysis with Python
14 minLesson 18
Handling Missing Data in Time Series: Proven Techniques for Accurate Analysis
14 minLesson 19
Understanding Stationarity and the Augmented Dickey-Fuller Test in Time Series Analysis
13 minLesson 20
Understanding Autocorrelation and Partial Autocorrelation in Time Series Analysis
10 minLesson 21
Seasonal Decomposition in Python: Techniques for Time Series Analysis and Interpretation
15 minLesson 22
Understanding Autoregressive, Moving Average, and ARMA Models for Time Series Forecasting
17 minLesson 24
Seasonal ARIMA and SARIMAX in Python: A Guide to Time Series Forecasting
12 minLesson 25
Understanding Exponential Smoothing and Holt-Winters Forecasting Models in Python
14 minLesson 26
Understanding Model Diagnostics and Residual Analysis for Time Series Forecasting in Python
12 minLesson 27
Creating Lag and Rolling Features for Time Series Analysis in Python
12 minLesson 28
Encoding Seasonality in Time Series Data Using Fourier Terms for Accurate Modeling
11 minLesson 29
Supervised Learning for Time Series in Python: Data Preparation and Model Setup
14 minLesson 30
Linear Regression and Regularization Techniques for Accurate Forecasting in Machine Learning
14 minLesson 31
Using Random Forest and XGBoost for Accurate Time Series Forecasting
15 minLesson 32
Walk-Forward Validation in Python: A Clear Guide for Time Series Model Evaluation
16 minLesson 33
Understanding 7 Key Forecast Accuracy Metrics for Evaluating Models in Python
10 minLesson 36
Understanding Convolutional Neural Networks for Time Series Analysis in Christian Data Studies
11 minLesson 38
Sequence-to-Sequence Forecasting in Python: Deep Learning for Time Series Prediction
10 minLesson 42
Using Multilayer Perceptrons for Time Series Forecasting in Christian Analytics
30 minLesson 1
Python Basics for Supply Chain Analytics
23 minLesson 2
Numbers, Dates, and Quantities in Operations
24 minLesson 3
Control Flow for Operational Decision Logic
21 minLesson 4
Functions for Supply Chain Calculations
22 minLesson 6
Loading and Exploring Supply Chain Datasets
19 minLesson 7
Order-Level and Demand Analysis in Supply Chain Operations Analytics | Full Training
22 minLesson 8
Daily and Monthly Demand Aggregations in Supply Chain Analytics
25 minLesson 9
Inventory Level Tracking with Pandas
23 minLesson 11
Handling Missing and Dirty Operations Data
23 minLesson 12
Introduction to SQL for Supply Chain Analysts
22 minLesson 13
Joining Orders, Inventory, and Supplier Tables in Supply Chain Analytics
24 minLesson 14
SQL vs Pandas for Operational Reporting: Key Differences & Best Practices
24 minLesson 15
Mastering Core Supply Chain Views for Enhanced Operations Analytics
26 minLesson 20
Introduction to Demand Forecasting Data
24 minLesson 21
Time Series Decomposition Techniques for Accurate Demand Forecasting in Supply Chain
31 minLesson 22
Moving Average and Exponential Smoothing Models in Supply Chain Analytics
23 minLesson 23
ARIMA and SARIMA for Demand Forecasting in Supply Chains
26 minLesson 24
Forecast Accuracy Evaluation and Monitoring in Supply Chain Operations
28 minLesson 25
Understanding Inventory Dynamics in Supply Chain Analytics
26 minLesson 26
Safety Stock and Reorder Point Modeling
25 minLesson 27
ABC Inventory Classification in Supply Chain Analytics
22 minLesson 30
Supplier Performance Metrics in Supply Chain Analytics
31 minLesson 31
Lead Time Variability Analysis in Supply Chains
19 minLesson 32
On-Time Delivery and Fulfillment Rates in Supply Chain Analytics
18 minLesson 36
Building Supply Chain Dashboards with Streamlit
25 minLesson 37
Transforming Operations Notebooks into Scalable Production Pipelines in Supply Chain Analytics
22 minLesson 38
End-to-End Supply Chain Analytics Project
22 minLesson 1
Python Basics for Banking
21 minLesson 2
Numbers, Strings, and Money in Banking
22 minLesson 3
Implementing Control Flow for Transaction Logic in Python: Banking and Finance Applications
26 minLesson 4
Using Python Functions to Automate Financial Rules in Banking and Finance
21 minLesson 5
Effective Error Handling in Banking Systems Using Python for Secure Financial Software
24 minLesson 6
How to Load and Analyze Bank Datasets in Python for Financial Insights
21 minLesson 7
Transaction-Level Financial Data Analysis Using Python for Banking and Finance
18 minLesson 8
How to Aggregate Daily and Monthly Financial Data Using Python for Banking Analysis
20 minLesson 11
Effective Methods for Cleaning and Managing Missing Data in Banking Datasets Using Python
19 minLesson 12
Fundamentals of SQL for Banking Analysts: Essential Skills for Financial Data Analysis
31 minLesson 14
Comparing SQL and Pandas for Effective Financial Reporting and Data Analysis
22 minLesson 15
How to Build Core Banking Views with Python for Financial Data Management
26 minLesson 16
Analyzing Key Banking KPIs with Python: A Practical Guide for Finance Professionals
22 minLesson 17
Creating Automated Regulatory Reports for Banking Compliance Using Python
21 minLesson 19
Understanding End-of-Day Processing Logic in Banking with Python
20 minLesson 20
Fundamentals of Credit Risk Data Analysis in Banking Using Python
20 minLesson 22
Feature Engineering Techniques to Improve Credit Risk Models Using Python
20 minLesson 26
Understanding Rule-Based Fraud Detection in Banking: A Practical Python Guide
25 minLesson 29
Designing Effective Fraud Alert Thresholds for Banking Systems Using Python
20 minLesson 30
Fundamentals of Time Series Analysis for Banking Professionals Using Python
21 minLesson 31
Analyzing Transaction Trends and Seasonality in Finance Using Python
23 minLesson 32
Applying Moving Averages and Smoothing Techniques to Financial Time Series in Python
20 minLesson 34
Automating Banking Workflows with Python: Practical Training for Financial Efficiency
19 minLesson 35
Automating Banking and Finance Workflows with Python Job Scheduling
11 minLesson 8
1 Introduction to Machine Learning in Python
15 minLesson 14
Understanding Accuracy, Precision, Recall, F1 Score, and ROC Curve for Model Evaluation in Python
28 minLesson 17
Master Python Tuples: Fundamentals and Practical Applications Explained
11 minLesson 24
13 - Importing Modules in Python: Fundamentals for Beginners
15 minLesson 25
Python Fundamentals: Build a Temperature Converter Step-by-Step
13 minLesson 26
Python Fundamentals: Create a Simple Calculator Step by Step
16 minLesson 27
16 - Python Fundamentals: Simple Bank System Mini Project Tutorial
12 minLesson 29
Understanding Simple and Multiple Linear Regression in Python for Bible Study Applications
13 minLesson 33
Understanding Ridge, Lasso, and ElasticNet Regularization in Python for Regression Analysis
16 minLesson 34
Predicting California Housing Prices with Python: A Step-by-Step Regression Guide
14 minLesson 40
Mastering Date and Time Basics in Python | Week 03–04 Data Handling
13 minLesson 44
Understanding K Nearest Neighbors (KNN) in Python: A Step-by-Step Guide for Classification
13 minLesson 45
2 - Removing Duplicates in Python: Data Cleaning Techniques
16 minLesson 46
Understanding Decision Trees and Random Forests in Python for Bible Teaching Applications
12 minLesson 61
Master Hyperparameter Tuning with GridSearchCV in Python for Optimal ML Models
3 minLesson 63
03 Inspect Columns and Summary Statistics in Pandas
13 minLesson 68
Understanding Principal Component Analysis (PCA) in Python: A Comprehensive Tutorial
15 minLesson 69
Customer Segmentation Using PCA and KMeans Clustering in Python: A Step-by-Step Guide
10 minLesson 73
Fundamentals of Descriptive Statistics in Python for Data Analysis
11 minLesson 75
Understanding Gradient Boosting and Implementing XGBoost in Python for Predictive Modeling
13 minLesson 83
Foundations of Neural Networks and Multilayer Perceptrons (MLP) Explained in Python
17 minLesson 85
Classifying Fashion MNIST Images with TensorFlow and Keras in Python
23 minLesson 1
Introduction to Technical Analysis for Finance and Stock Market Analytics
35 minLesson 2
Understanding Financial Markets and Instruments: Key Concepts and Analytics
24 minLesson 3
Types of Financial Data: OHLCV, Fundamentals, and Sentiment Explained
26 minLesson 4
Financial Analytics Workflow Using Python: Step-by-Step Training for Beginners
24 minLesson 8
Numerical Analysis with NumPy for Financial Data: Training and Applications
20 minLesson 9
Introduction to Pandas for Stock Data Analysis
24 minLesson 11
Structure of Stock Market Datasets for Analytical Training
24 minLesson 12
Understanding OHLCV Data in Finance: Open, High, Low, Close, and Volume Explained
23 minLesson 15
Assessing Financial Data Quality: Techniques and Best Practices for Accurate Analysis
23 minLesson 20
Preparing Clean Financial Datasets for Analysis: Step-by-Step Data Cleaning Guide
25 minLesson 44
Scheduling Financial Data Updates for Automated Analytics
23 minLesson 46
Introduction to Time Series in Finance: Key Concepts and Applications
28 minLesson 49
Moving Averages and Smoothing Techniques in Stock Market Analysis
23 minLesson 50
Seasonal Patterns in Financial Markets: Understanding Recurring Trends
22 minLesson 57
Designing Financial Analytics Dashboards: Principles, Tools, and Best Practices
28 minLesson 60
Exporting Financial Reports with Python: Step-by-Step Training Guide
14 minLesson 1
1 Capstone ML Project in Python: Build and Evaluate a Machine Learning Model
21 minLesson 3
Comprehensive Guide to Training Machine Learning Models with Scikit-Learn in Python
12 minLesson 4
2 Train-Test Split in Python: Step-by-Step Guide for Machine Learning Beginners
10 minLesson 5
3 Cross-Validation in Python: Machine Learning Model Evaluation Techniques
21 minLesson 7
Simple Linear Regression Model in Python with scikit-learn
11 minLesson 8
Polynomial Regression in Python: Complete Guide for Machine Learning Beginners
11 minLesson 14
Titanic Survival Prediction with Python: Data Analysis & Machine Learning Basics
13 minLesson 15
Building a Heart Disease Classification Model in Python: Step-by-Step Machine Learning Guide
12 minLesson 16
Handling Missing Values and Data Imputation Techniques in Python for Machine Learning
12 minLesson 18
Feature Scaling and Pipeline Construction in Python for Effective Machine Learning
15 minLesson 22
Understanding KMeans Clustering in Python: A Guide to Unsupervised Machine Learning
12 minLesson 23
Master DBSCAN & Hierarchical Clustering in Python for Unsupervised Learning
12 minLesson 26
Master Support Vector Machines (SVM) in Python for Advanced Machine Learning
9 minLesson 28
Understanding Gradient Boosting with LightGBM in Python for Advanced Machine Learning
15 minLesson 29
Master Ensemble Learning & Stacking Techniques in Python for Better Machine Learning Models
10 minLesson 30
Building a Credit Card Fraud Detection System with Python and Machine Learning
20 minLesson 2
How to Install and Set Up the OpenAI Python SDK: A Step-by-Step Guide
20 minLesson 3
Mastering OpenAI Models: Enhance AI Responses with Python Embeddings
17 minLesson 4
Understanding Chat Completions API: Building Conversational AI with OpenAI
16 minLesson 6
Master OpenAI Embeddings API with Effective Python Error Handling
25 minLesson 7
Understanding Vector Search and Semantic Similarity in AI and Machine Learning
18 minLesson 10
How to Use OpenAI Whisper for Accurate Speech-to-Text Transcription
15 minLesson 11
How to Build Text-to-Speech Systems Using GPT and OpenAI APIs for Christian Teaching Tools
4 minLesson 12
OpenAI Function Calling Explained with Error Handling in Python
23 minLesson 13
Mastering OpenAI Tools API: Seamlessly Integrate External Apps with Python
23 minLesson 14
Master the OpenAI Assistants API: Build Interactive & Intelligent Python Applications
25 minLesson 16
Managing Errors and Rate Limits in OpenAI API Integrations for Reliable Applications
4 minLesson 17
OpenAI Python Error Handling and API Best Practices
22 minLesson 18
How to Build a Simple AI Assistant Using OpenAI and Python: Step-by-Step Tutorial
16 minLesson 19
How to Diagnose and Resolve Common OpenAI API Issues for Reliable Integration
16 minComprehensive BeautifulSoup Tutorial for Web Scraping with Python
24 minIntroduction to NetworkX in Python for Graph Analysis and Network Science
19 minIntroduction to OpenCV in Python: Essential Computer Vision Techniques Explained
18 minEssential Python Pillow Techniques for Image Processing and Editing
20 minMastering Polars for Efficient Big Data Analysis in Python
21 minComprehensive PyArrow Training for Efficient Data Processing in Python
16 minUnderstanding Pydantic: Efficient Data Validation and Management in Python
21 minEssential PyTorch Training Techniques for Effective Neural Network Development
22 minLesson 1
Comprehensive Guide to Automating Word Documents with python-docx in Python
14 minLesson 3
Comprehensive openpyxl Tutorial for Automating Excel with Python
14 minLesson 4
How to Read Excel Files in Python Using the xlrd Library: Step-by-Step Tutorial
17 minLesson 5
Comprehensive Guide to Using pypdf for PDF File Management in Python
14 minLesson 6
Comprehensive Guide to Using Python xlsxwriter for Excel File Creation and Automation
20 minLesson 9
Step-by-Step Guide to Setting Up the OpenAI API with Python for Beginners
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