Course Overview

Python Language – Use in AI is an 8-week course designed for M.Tech, M.Sc, and MCA students, as well as professionals in IT, BFSI, consulting, and fintech industries. This course delves into Python's key role in developing AI technologies. Participants will gain hands-on experience with Python programming, data handling, machine learning, deep learning, and natural language processing (NLP) using popular libraries like TensorFlow, Keras, Scikit-learn, NumPy, and Pandas.

Course Goals

This course aims to provide participants with a thorough understanding of Python as a foundational tool in AI, enabling them to build and deploy Python-based AI solutions. Through practical applications and real-world examples, participants will become proficient in using Python to solve complex AI problems.

Program Objectives

• Mastery of Python for AI: Gain an in-depth understanding of Python's capabilities in AI development.
• Practical Application Skills: Learn to apply Python in machine learning, deep learning, and NLP projects.
• Innovative Problem Solving: Develop the ability to tackle real-world problems with Python-driven AI solutions.

Program Structure

• Module 1: Introduction to Python for AI
  • Fundamentals of Python in AI applications
  • Setting up the environment and learning basic Python programming concepts
• Module 2: Data Handling and Manipulation
  • Using NumPy and Pandas for efficient data analysis
  • Visualizing data with Matplotlib and Seaborn to gain insights
• Module 3: Introduction to Machine Learning with Python
  • Basics of machine learning
  • Implementing machine learning algorithms using Scikit-learn
  • Evaluating model performance and tuning algorithms
• Module 4: Deep Learning with Python
  • Understanding neural networks and their architecture
  • Building and training deep learning models with TensorFlow and Keras
• Module 5: Natural Language Processing (NLP)
  • Introduction to NLP and its applications
  • Using NLTK and spaCy for text analysis and processing
  • Implementing NLP projects such as sentiment analysis and text classification
• Module 6: Capstone Projects and Advanced Topics
  • Integrating AI in web applications
  • Discussing ethical considerations in AI development
  • Capstone project: Designing and implementing an AI solution using Python

Eligibility

• Students: M.Tech, M.Sc, and MCA students specializing in IT, computer science, or related fields.
• Professionals: E0 & E1 level professionals in BFSI, IT services, consulting, and fintech IT services.

Learning Outcomes

• Enhanced Python Skills: Attain advanced proficiency in Python for AI development.
• AI Implementation Expertise: Gain the skills needed to implement and manage Python-based AI projects effectively.
• Strategic Insight: Understand how to strategically leverage Python in AI to drive innovation and business success.