Python for AI with Scikit-Learn

Aim

Program Objectives

Program Structure

1. Python Programming for AI
   • Advanced Python features and libraries for AI.
   • Efficient data structures and algorithms for AI applications.
2. Data Handling and Analysis with Pandas and NumPy
   • Manipulating and processing data using Pandas.
   • Numerical operations for AI with NumPy.
3. Machine Learning Foundations with Scikit-Learn
   • Supervised learning techniques: Regression and Classification.
   • Unsupervised learning techniques: Clustering and Dimensionality Reduction.
4. Model Optimization and Evaluation
   • Hyperparameter tuning using GridSearchCV and RandomizedSearchCV.
   • Performance metrics and model evaluation strategies.
5. Ensemble Methods and Advanced Modeling
   • Implementing ensemble methods for robust predictions.
   • Advanced machine learning models for complex problem-solving.
6. Natural Language Processing with Scikit-Learn and NLTK
   • Text data preprocessing and feature extraction.
   • Building and tuning NLP models for text classification and sentiment analysis.
7. Capstone Project
   • Applying learned techniques to a real-world AI challenge.
   • Collaboration with industry experts and academic peers.

Who Should Enrol?

Program Outcomes

Fee Structure

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