Course Overview

This syllabus outlines the topics covered in the programming course.

Core Python (Week 1-4)

• Introduction to Python
• Variables and Data Types
• Control Structures (if, for, while)
• Functions and Modules
• Input/Output

Week 3-4: Advanced Python

• Object-Oriented Programming (OOP) in Python
• File Handling
• Data Structures (Lists, Dictionaries, Sets, Tuples)
• Comprehensions and Generators
• Python Libraries (e.g., NumPy, Pandas)

Week 5-6: Advanced Topics

• Decorators and Context Managers
• Functional Programming in Python
• Concurrency and Parallelism
• Python Package Management (e.g., pip)

Week 7-8: Web Development with Python

• Introduction to Web Development
• Web Frameworks (e.g., Django, Flask)
• Database Integration (e.g., SQLite, PostgreSQL)
• RESTful APIs

Data Science (Week 9-16)

• Data Cleaning and Preprocessing
• Exploratory Data Analysis (EDA)
• Data Visualization (e.g., Matplotlib, Seaborn)

Machine Learning (Week 17-24)

• Ensemble Methods (Random Forest, Gradient Boosting)
• Support Vector Machines (SVM)
• Neural Networks
• Hyperparameter Tuning
• Text Preprocessing
• Named Entity Recognition
• Word Embeddings (e.g., Word2Vec, GloVe)

Deep Learning and AI (Week 25-32)

• TensorFlow and Keras
• PyTorch
• Building Neural Networks
• Recurrent Neural Networks (RNNs)

Week 32-33: Artificial Intelligence

• AI in Practice
• Ethics and Bias in AI
• AI Applications and Future Trends
• Heuristic search algorithms (e.g., A* search)