Track 12 of 14
Master machine learning and AI. Build predictive models, analyze data, and solve complex problems.
Data Science is transforming industries. In this comprehensive 16-week program, you'll master machine learning, deep learning, and predictive analytics.
From Python for data science to supervised and unsupervised learning, neural networks, and big data processing, this course covers the entire data science toolkit. You'll build real-world ML models and deploy them to production.
Master Python and data science libraries (NumPy, Pandas, Scikit-learn)
Build supervised learning models (regression, classification)
Implement unsupervised learning algorithms (clustering, dimensionality reduction)
Create neural networks and deep learning models with TensorFlow/PyTorch
Handle feature engineering and model optimization
Evaluate and validate machine learning models
Deploy ML models to production environments
Work with big data and distributed computing frameworks
₹10-18L
₹12-20L
₹14-25L
Week 1-2
• Python basics
• NumPy
• Pandas
• Data manipulation
Project: Data Cleaning Project
Week 3-4
• Statistical concepts
• Probability
• Visualization
• EDA
Project: Comprehensive Data Analysis
Week 5-7
• Regression
• Classification
• Decision trees
• Ensemble methods
Project: Build Predictive Models
Week 8-9
• Clustering
• Dimensionality reduction
• Anomaly detection
• PCA
Project: Clustering & Pattern Analysis
Week 10-12
• Neural networks
• CNNs
• RNNs
• Transfer learning
Project: Build Deep Learning Model
Week 13-14
• NLP basics
• Time series
• Recommendation systems
• Feature engineering
Project: Advanced ML Project
Week 15-16
• Model deployment
• MLOps
• Cloud ML
• Best practices
Project: Capstone Data Science Project
Primary language for data science and ML
Advanced Level
Machine learning library for python
Advanced Level
Deep learning frameworks
Advanced Level
Interactive notebook for data science
Beginner Level