Course Outline: Mastering Applied ML for the AI Era (No Math Overload) – 8 Weeks
🚀 Learn by Doing | 7+ Real-World Projects | Hands-On Python Implementation
Mode: Online
📅 Week 1: Python & Data Foundations
🔹 Python for ML: Lists, Loops, Functions, NumPy
🔹 Pandas for Data Analysis & Manipulation
🔹 File Handling: CSV, JSON, Excel
🔹 Mini Project: Analyzing Sales Data with Pandas
📅 Week 2: Data Cleaning & Feature Engineering
🔹 Handling Missing Data & Outliers
🔹 Encoding Categorical Variables
🔹 Feature Scaling & Selection
🔹 Mini Project: Cleaning & Preparing a Real-World Dataset
📅 Week 3: Data Visualization & Storytelling
🔹 Mastering Matplotlib & Seaborn
🔹 Interactive Visualizations with Plotly
🔹 Data Storytelling Techniques for AI
🔹 Mini Project: Visualizing Customer Churn Trends
📅 Week 4: Machine Learning and AI Applications
🔹 ML Workflow: Data → Model → Evaluation
🔹 Supervised vs. Unsupervised Learning
🔹 Hands-On with Scikit-Learn
🔹 Project 1: Customer Churn Analysis
Other Benefits:
🔹 Free eBook: Python for Data Science
Number of Pages: 200+
Modules Covered: 15
Real-world examples: 20+
🔹 Complete Course Material
🔹 All codes available
🔹 Mentorship Session
Starting: Coming soon
📅 Week 5: Regression & Classification Models
🔹 Linear & Logistic Regression
🔹 Decision Trees & Random Forest
🔹 Model Evaluation Metrics (RMSE, R², Precision, Recall, F1-score)
🔹 Project 2: House Price Prediction
🔹 Project 3: Loan Default Risk Classification
📅 Week 6: Advanced ML and Model optimization
🔹 Hyperparameter Tuning (GridSearchCV)
🔹 Feature Importance & Model Performance
🔹 Handling Imbalanced Datasets (SMOTE, Weighted Classes)
🔹 Project 4: Credit Card Fraud Detection
📅 Week 7: Unsupervised Learning and Clustering
🔹 K-Means & Hierarchical Clustering
🔹 Dimensionality Reduction (PCA)
🔹 Real-World Applications of Unsupervised ML
🔹 Project 5: Customer Segmentation with K-Means
📅 Week 8: ML Model Deployment & AI-Powered Apps
🔹 Saving & Loading ML Models
🔹 Building a Web App with FastAPI & Flask
🔹 Deploying AI Apps using Streamlit
🔹 Project 6: Employee Attrition Prediction (Full Deployment)