Python for Deep Learning and AI

Course Objective

This course introduces PGDM students to Python programming for deep learning and artificial intelligence applications. It equips learners with foundational coding skills and applied knowledge of neural networks, machine learning, and AI systems using popular Python libraries. Students will work on real-world business problems using digital tools, data analytics, and automation techniques.

Learning Outcomes

  • Write Python programs for data processing, visualization, and automation.
  • Use libraries like NumPy, Pandas, Matplotlib, TensorFlow, and Keras.
  • Build and train machine learning and deep learning models.
  • Apply AI models to solve real-world business problems across marketing, finance, and operations.
  • Interpret and communicate AI-driven insights with clarity and strategic thinking.

Python for Deep Learning and AI Syllabus T30

Session No. Topics Tool/Reading/Activity Skill Focus
1 Introduction to Python & AI in Business Colab + Notebook Strategic Thinking
2 Python Basics: Variables, Data Types, Control Flow Notebook Practice Programming Logic
3 Functions, Loops, and Error Handling Coding Lab Structured Programming
4 NumPy and Matrix Operations NumPy Labs Numerical Computing
5 Data Analysis with Pandas Pandas DataFrame Exercises Business Data Handling
6 Data Visualization with Matplotlib & Seaborn Charting Labs Insight Communication
7 Introduction to Machine Learning Scikit-learn Basics Modeling Concepts
8 Supervised Learning: Regression and Classification Scikit-learn Project Predictive Analytics
9 Unsupervised Learning: Clustering & Dimensionality Reduction PCA/KMeans Labs Exploratory Analysis
10 AI Ethics and Responsible AI Discussion & Cases Leadership Awareness
11 Neural Networks Introduction with Keras Sequential API Lab Deep Learning Basics
12 Training Deep Neural Networks Keras Fit/Evaluate Model Optimization
13 CNNs for Image Recognition TensorFlow & Keras Visual AI Applications
14 RNNs for Sequential Data Text & Time Series Models Temporal Intelligence
15 AI in Finance and Marketing Use Case Demos Domain Adaptability
16 Natural Language Processing with Python NLP Toolkit Text Mining
17 AI-Powered Automation Tools OpenAI API & Streamlit Workflow Automation
18 AI Strategy for Business Leaders Strategic Mapping Business Impact
19 Capstone Project – Build & Present AI Model Student Teams Solution Design
20 Final Presentations & Feedback Evaluation Day Strategic Communication

Textbook & Resources

Primary Tools & Libraries:
  • Python 3.x, Jupyter Notebooks, NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Keras
Reference Books:
  • Deep Learning with Python by François Chollet
  • Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow by Aurélien Géron