Full Stack AI & Machine Learning

Master Python, ML, Deep Learning, LLMs, RAG & AI Agents· Live Demo Day.

Supreeth Bandi

aiminds360

English

Certification

2000 Learners

9 Weeks

Course Overview

Master the complete AI & Machine Learning stack — from Python to production AI agents.

This is not a theory course. Every week you code, build, and ship.

In 9 weeks you'll cover the entire modern AI stack — data science, machine learning, deep learning, NLP, large language models, RAG, fine-tuning, and agentic AI — and graduate with 6 real projects.

🧱 What you'll master, week by week:

Weeks 1–2: Python, Pandas, NumPy, SQL, EDA & data visualisation

Weeks 3–4: Machine Learning — regression, trees, ensembles, SVM, clustering, model deployment

Week 5: NLP, neural networks, CNNs, RNNs, LSTMs, fraud detection

Week 6: LLMs, transformers, BERT vs GPT, prompt engineering, Chain-of-Thought

Week 7: Fine-tuning with LoRA/QLoRA, RAG pipelines, RAGAS evaluation, model interpretability

Week 8: AI Agents — LangChain, LangGraph, MCP, A2A, multi-agent orchestration

Week 9: Live capstone demo in front of industry professionals

🛠️ 6 projects you'll graduate with:

Full EDA report on real data

End-to-end supervised ML pipeline

Live NLP text classifier

Fraud detection ML pipeline

Team GenAI industry solution

Final Capstone — presented live on Demo Day

👤 Who this is for: Developers, analysts, career switchers, and graduates who want to break into AI with a full portfolio — not just a certificate

FAQ

No. This course starts from Python basics and builds up progressively. If you can use a computer and have basic logic skills, you're ready.

Python is used throughout — from data manipulation with Pandas and NumPy to building neural networks with PyTorch and TensorFlow and deploying AI agents with LangChain.

It's a cohort-based live programme running 5 days a week (Monday–Friday) for 9 weeks. Most days are live classes; some project days are self-paced with guided walkthroughs.

You will complete 6 deliverables: a full EDA report, a supervised ML pipeline, an NLP text classifier, a fraud detection pipeline, a team GenAI industry solution, and a final capstone presented live on Demo Day.

Yes. AiMinds360 certificates are awarded on Demo Day upon successful completion of the programme and final capstone presentation.

Classes run Monday to Friday. Each live session is approximately 1.5–2 hours. On project days you should budget 3–4 hours to complete your deliverable.

Python 3.x, VS Code or Jupyter Notebook, and a Google account for Colab. All required libraries (Pandas, PyTorch, LangChain, etc.) are free and open-source. Full setup instructions are provided before Day 1.

Recordings are provided after each live session so you can catch up at your own pace before the next class.

Course curriculum

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Course Curriculum

Flexible batches for you

Pick a start date that fits your schedule.

22 JUN Full Stack AIML Course- June 22nd Batch Weekday Mon - Friday (9 Weeks) 07:00 PM - 08:00 PM (America/Chicago) Open 25 left 23 JUN Fullstack AIML Course - June 23rd Batch Weekday Mon - Friday (9 Weeks) 07:00 PM - 08:00 AM (IST) Open 30

Requirment

Basic computer literacy — ability to install software and navigate files
No prior ML or AI experience required
A laptop or desktop with internet access (Windows, Mac or Linux)
Willingness to commit 5 days a week for 9 weeks
Google account (for Google Colab access)

Outcomes

Build and deploy end-to-end machine learning pipelines from scratch
Master Python, Pandas, NumPy, SQL and data visualisation for data science
Train and evaluate ML models including regression, decision trees, ensembles, SVM and clustering
Build deep learning models using CNNs, RNNs and LSTMs with PyTorch and TensorFlow
Understand and apply LLMs, transformers, BERT and GPT architectures
Engineer effective prompts using Chain-of-Thought, ReAct and few-shot techniques
Fine-tune language models using LoRA and QLoRA with PEFT
Build and evaluate production-grade RAG pipelines with RAGAS metrics
Design and deploy AI agents using LangChain, LangGraph, MCP and A2A protocols
Deploy ML models as REST APIs using Flask, FastAPI and Docker
Complete 6 real projects including a live-demoed final capstone
Graduate with a verified AiMinds360 certificate and a portfolio ready for job applications

Instructor

Supreeth Bandi

0 Student
2 Courses

Supreeth Reddy is a Senior Gen AI Architect, helping engineering teams harness the power of AI. With a background spanning AI research, data science, and entrepreneurship, he has built everything from real-time AI-powered sleep-tech products as Co-Founder of Serene AI to CNN-based robotics classifiers at Worcester Polytechnic Institute. A Best Paper award winner at the IJCCI Conference in Portugal, Supreeth brings both research depth and hands-on product experience to every problem he tackles.

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