Understand deeply. Build deliberately.
The NextGen AI Fellowship is a 6-month, full-time, in-person program in Noida. You will study 8 subjects, starting from programming and AI basics and finishing with a real-world capstone project. Each subject feeds the next: programming skills support data science, data science supports machine learning, machine learning leads into generative AI, and cloud, security and DevOps skills turn prototypes into working products.
Duration
24 weeks (6 months)
Subjects
8 core subjects plus a 4-week capstone project
Weekly Load
about 25 hours (live classes, guided labs, self-study and project work)
Format
instructor-led sessions with hands-on labs, weekly assessments, mentor check-ins
Who can join
basic computer literacy and logical thinking; coding experience is helpful but not required
You leave with
a capstone product, a GitHub portfolio, and a fellowship certificate
Month-by-Month Plan
Foundations
Programming, Digital Technologies, AI foundations
A tested Python API project and a neural network from scratch
Data & Algorithms
Data Science, Programming (data structures, TypeScript)
A data analysis report and dashboard
Learning from Data
Machine Learning, AI (deep learning), Cloud intro
An end-to-end ML model served as an API
Scale & Intelligence
Cloud, Generative AI intro, CI/CD
A cloud-deployed ML service with an automated pipeline
Applied GenAI & Security
Generative AI, Cybersecurity
A deployed RAG/agent application with evaluation and security review
Capstone
Real projects: integration of all subjects
You combine everything into one real AI product and present it on Demo Day
The 8 Core Subjects
Artificial Intelligence
Weeks 3-4 and 9-10 • ~40 hrs
Foundational AI concepts, neural networks, and modern deep learning architectures.
- build a neural network from scratch
- implement deep learning models in PyTorch
- use transformers and transfer learning
- check AI systems for bias and fairness.
Machine Learning
Weeks 9-12 • ~50 hrs
Supervised and unsupervised learning, predictive modeling, and algorithm optimization using scikit-learn.
- run the full ML workflow
- train regression, classification and ensemble models
- tune and validate models
- serve a model as an API.
Generative AI
Weeks 13-14 and 17-20 • ~60 hrs
LLMs, prompt engineering, RAG, and building AI agents with LangChain.
- design reliable prompts
- build RAG pipelines with vector databases
- build and orchestrate AI agents
- deploy and monitor an LLM application.
Data Science
Weeks 5-8 • ~40 hrs
Data processing, statistical analysis, and visualization.
- clean and transform data with pandas and SQL
- apply statistics to support decisions
- build clear dashboards
- deliver an end-to-end analysis with a business story.
Cybersecurity
Weeks 17-20 • ~40 hrs
Network security, threat intelligence, and secure coding practices. All lab work is defensive and done in sandboxed environments.
- apply core security principles
- write secure code
- fix common vulnerabilities (OWASP Top 10)
- secure cloud and AI applications.
Cloud Computing
Weeks 11-16 • ~60 hrs
AWS/GCP infrastructure, Docker, Kubernetes, and serverless architectures.
- use core cloud services
- containerize applications with Docker
- deploy on Kubernetes
- build serverless solutions
- deploy an ML service with monitoring.
Programming
Weeks 1-8 • ~70 hrs
Advanced Python, TypeScript, and data structures and algorithms. Starts on day one and supports every other subject.
- write clean, tested Python
- build REST APIs
- implement core data structures
- write type-safe TypeScript.
Digital Technologies
Weeks 1-2 and 15-16 • ~30 hrs
Version control, CI/CD pipelines, and agile software development.
- collaborate with Git and GitHub
- work in agile sprints
- build pipelines that test and deploy automatically.
CAPSTONE (final 4 weeks)
Small teams work in agile sprints to design, build, secure and deploy a real AI-powered product, then present it on Demo Day. You deliver: a working deployed application, a GitHub repository with tests and CI/CD, technical documentation, and a live demonstration.
CERTIFICATE
To earn the fellowship certificate: minimum 80% attendance, 60% or higher overall score, all mini-projects submitted, and a completed capstone with Demo Day presentation.
TOOLS
Python, TypeScript, SQL, scikit-learn, PyTorch, LangChain, Docker, Kubernetes, AWS/GCP, Git and GitHub, all provided free during the program.
* Week allocations and hours are indicative and may be adjusted for each batch.
50 Seats. 6 Months. Fully Free.
Six months. Fully residential. Pan-India.