AI for Everyone (Batch-05)

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Course Content

Class 01 – AI Engineering Overview | Anaconda IDE Installation | Python Basics (Print, Comments, Variables, Data Types)

  • AI for Everyone (Batch-05) – Session 01
    02:27:44

Class 02 – Python Data Types | Escape Sequences | Built-in Functions | String Indexing & Slicing | Data Engineer Skills Discussion

Class 03 – Python Data Types | Built-in Functions (Lists, Sets, Tuples, Dicts, Booleans) | Comparison Operators | Conditional Statements

Class 04 – Python Loops | For & While Loops | Loop Controls (Break, Continue, Pass) | Mini Projects (Even/Odd, Guessing Game)

Class 05 – Introduction to Pandas | Exploratory Data Analysis (EDA) | Data Pre-processing | Importing Excel/CSV Files | Visualizations with Matplotlib & Seaborn | Correlation & Heatmaps

Class 06 – Real-World Python Projects – PDF Merger, Watermarking, Text/Image Extraction | Email Sender with Static/Dynamic Content | Audio-to-Text Transcription & Urdu Translation | Use Cases & Opportunities Overview

Class 07 – Introduction to Machine Learning & Its Types (Supervised, Unsupervised, Reinforcement) | Features Explained | Converting Categorical to Numerical Data

Class 08 – Evaluation Metrics (Confusion Matrix, Accuracy, Precision, Recall, F1 Score) | Feature Scaling | Logistic Regression & SVM – Theory & Implementation | Making Predictions on New Data

Class 09 – Machine Learning: Standardization & Normalization | Decision Tree – Scikit-Learn & Manual Implementation

Class 10 – Machine Learning: Random Forest Implementation | Underfitting vs. Overfitting | Bias-Variance Tradeoff | ROC & AUC Curves | Introduction to KNN