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Bootcamp: Data Science, Machine Learning & MLOps
Comprehensive hands-on training in Data Science, Machine Learning, Deep Learning, and Artificial Intelligence using Python. This course is designed to help learners build a strong foundation in core ML concepts, work with real-world data, develop intelligent models, explore Generative AI, and build practical AI agents like modern ML engineers.
Duration
4 months
Level
intermediate
Type
Live Course
Next Batch
June 26, 2026
Who is eligible for this course?
Wants to learn Python, Data Science, Machine and Deep Learning
CSE and non-CSE students
Software Developers
Test Engineers / QA
Network Engineers
Cloud Engineers
Who wants to excel in their industry standard ML and AI knowledge
Course Highlights
Master Python for data analysis and manipulation
Implement machine learning algorithms from scratch
Build predictive models using scikit-learn
Perform advanced data visualization
Get familiar with Deep Learning
Start your NLP journey
Work with big data using distributed computing
Deploy machine learning models to production
Build end-to-end data science pipelines
Weekly doubt clearing sessions
Build and deploy AI agents
Live Class Schedule
Friday and Tuesday
9:00 PM - 11:00 PM
Meet Your Mentors
Course Curriculum
Python FundamentalsFree Preview
Introduction to Machine LearningFree Preview
Python Fundamentals
Data Science
Learning Roadmap
Phase 1: Fundamentals
Build strong data science foundations
Python Programming
2 weeks
Data Types
Functions
OOP
Mathematics
2 weeks
Statistics
Linear Algebra
Calculus
Data Analysis
2 weeks
Pandas
NumPy
Visualization
Phase 2: Machine Learning
Master core ML concepts
Supervised Learning
2 weeks
Classification
Regression
Validation
Unsupervised Learning
2 weeks
Clustering
Dimensionality Reduction
PCA
Model Evaluation
1 week
Metrics
Cross-validation
Hyperparameter Tuning
Phase 3: Deep Learning
Explore neural networks
Neural Networks
2 weeks
Architectures
Training
Optimization
Computer Vision
2 weeks
CNNs
Object Detection
Image Segmentation
NLP
2 weeks
Text Processing
Transformers
BERT
Phase 4: Production & Deployment
Deploy ML systems
MLOps
2 weeks
Model Serving
Monitoring
Version Control
Big Data
1 week
Spark
Distributed Computing
Data Pipelines
Project
2 weeks
End-to-end Implementation
Documentation
Presentation