Master ML, DL, NLP, GenAI & MLOps with real-world projects.
Get practical AI skills. Build and deploy fast.
Why Choose This Course?
Master the complete AI development cycle from ML to MLOps and GenAI with industry-relevant tools.
In-Depth Curriculum
From core Machine Learning foundations to Generative AI and MLOps, the curriculum is built for mastery.
Project-Driven
Apply what you learn through real-world, high-impact projects that showcase your practical skills.
Career-Ready
Build a professional portfolio, get one-on-one mentorship, and prepare for top AI roles in the industry.
Tech-Stack Aligned
Learn the same tools used by engineers at Google, Meta, and OpenAI—including MLflow, Hugging Face, and more.
Hands-on & Practical
No fluff—only deep, applicable knowledge through immersive learning, practice, and deployment.
Who Can Join This Course?
Whether you're just starting or upskilling, this course is built for your AI and Data career journey.
Graduates & Post-Graduates
Aiming for a Data Science or AI career? This course builds your foundation and portfolio from day one.
Working Professionals
Engineers, analysts, or developers looking to transition into Data Science, ML, or AI roles will benefit deeply.
ML & AI Aspirants
Designed for future ML Engineers, AI Developers, and researchers building real-world intelligent systems.
Python Learners
If you know basic Python and are motivated to learn, this course gives you the practical skills to thrive in AI.
9-Month AI/ML + GenAI Curriculum
Master Python, ML, DL, NLP, GenAI, and MLOps — step-by-step
Month 1
Python for Data Science & Math Basics
- Week 1: Python Essentials – NumPy, Pandas
- Week 2: Data Wrangling, Data Cleaning
- Week 3: Data Visualization (Matplotlib, Seaborn)
- Week 4: Statistics and Probability for DS
Month 2
Core Machine Learning
- Week 5: Supervised Learning – Regression
- Week 6: Classification Techniques (SVM, KNN, DT)
- Week 7: Unsupervised Learning – Clustering, PCA
- Week 8: Model Evaluation & Hyperparameter Tuning
Month 3
Advanced Machine Learning
- Week 9: Ensemble Models (RF, XGBoost, LightGBM)
- Week 10: Feature Engineering and Pipelines
- Week 11: Time Series Analysis
- Week 12: Model Deployment (Flask + Heroku)
Month 4
SQL, Big Data & Data Engineering
- Week 13: SQL for DS (Joins, CTEs, Windows)
- Week 14: Data Warehousing – ETL, Snowflake
- Week 15: Apache Spark, PySpark Basics
- Week 16: Airflow for Workflow Automation
Month 5
Deep Learning
- Week 17: Neural Networks, Backpropagation
- Week 18: CNNs for Image Classification
- Week 19: RNNs, LSTMs for Sequential Data
- Week 20: TensorFlow vs PyTorch
Month 6
NLP & Text Mining
- Week 21: Text Preprocessing, TF-IDF
- Week 22: Word Embeddings (Word2Vec, GloVe)
- Week 23: NER & Topic Modeling
- Week 24: BERT, Hugging Face Transformers
Month 7
Generative AI
- Week 25: Intro to GenAI & LLMs
- Week 26: GPT Architecture, Tokenization
- Week 27: Fine-tuning LLMs
- Week 28: Prompt Engineering, LangChain, RAG
Month 8
MLOps & Cloud
- Week 29: CI/CD in ML – MLflow, DVC
- Week 30: Docker & Kubernetes
- Week 31: AWS/GCP – S3, EC2, Vertex AI
- Week 32: Monitoring, Logging, Auto Scaling
Month 9
Capstone & Interview Prep
- Week 33: Resume, GitHub, Portfolio Setup
- Week 34: Mock Interviews & DS Case Studies
- Week 35–36: Final Capstone Project Presentation
Tools & Technologies Covered
Gain hands-on experience with the most in-demand technologies in AI, ML, and MLOps
Python
NumPy
Pandas
Scikit-learn
TensorFlow
PyTorch
SQL
Apache Spark
Hadoop
XGBoost
BERT
Hugging Face
GPT
Docker
Kubernetes
AWS
GCP
FastAPI
Git
Streamlit
Real Projects You’ll Build
Hands-on projects that strengthen your skills and showcase your job-ready experience.
What Our Students Say
Go Beyond Data. Master AI. Launch Your Career.
From foundational AI to advanced GenAI – all in one program.