Python for Data Science & AI: 8 Week Syllabus
Week 1: Introduction to Data Science with Python
- Setting up Python (Jupyter, Anaconda)
- Introduction to Data Science Workflow
- Python Refresher (lists, dicts, functions, loops)
- Libraries for Data Science (NumPy, Pandas, Matplotlib, Scikit-learn)
- Lab: Load and explore a CSV dataset
Week 2: NumPy for Numerical Computing
- Introduction to NumPy Arrays
- Array Operations (indexing, slicing, reshaping)
- Mathematical Operations (mean, sum, std, transpose)
- Broadcasting in NumPy
- Lab: Vector & Matrix Operations with NumPy
Week 3: Data Manipulation with Pandas
- Pandas DataFrame & Series Basics
- Importing Data (CSV, Excel, JSON)
- Data Cleaning (missing values, duplicates, type conversion)
- Filtering, Sorting & Grouping
- Lab: Analyze a Sales Dataset
Week 4: Data Visualization
- Introduction to Matplotlib & Seaborn
- Line, Bar, Histogram, Scatter, Pie Charts
- Advanced Plots (heatmaps, pairplots, boxplots)
- Customizing Plots (titles, labels, legends)
- Lab: Visualize COVID-19 or Stock Market Data
Week 5: Statistics & Exploratory Data Analysis (EDA)
- Descriptive Statistics (mean, median, mode, variance, std)
- Probability Distributions (normal, binomial, Poisson)
- Correlation & Covariance
- Outlier Detection
- Lab: Perform EDA on Titanic Dataset
Week 6: Machine Learning Basics
- Introduction to Machine Learning & AI
- Supervised vs Unsupervised Learning
- Linear Regression & Logistic Regression
- Train/Test Split & Model Evaluation (accuracy, precision, recall)
- Lab: Predict House Prices using Regression
Week 7: Advanced Machine Learning
- Decision Trees & Random Forests
- Clustering (K-Means)
- Introduction to Neural Networks
- Feature Scaling & Dimensionality Reduction (PCA)
- Lab: Customer Segmentation with K-Means
Week 8: Final Project & AI Applications
- Natural Language Processing (NLP) Basics (text cleaning, sentiment analysis)
- AI in Real World (recommendation systems, chatbots, image recognition)
- Deploying ML Models with Flask or Streamlit
- Final Project Options:
- Sentiment Analysis on Tweets
- Stock Price Prediction
- Movie Recommendation System
- Final Assessment & Presentation
