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AI & Data Analytics 6 months

Coding course in Faridabad · Online and Offline for Delhi NCR

ML, NLP, ChatGPT/Gemini labs and MLOps — from notebooks to interview-ready RAG case studies.

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PythonChatGPTGeminiLangChainMLOps
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AI & Data Analytics classroom and lab work
Program snapshot
6 months to complete
GenAI + RAG labs
MLOps
High-level interviews
AI / ML interview bank
The program

About this program

From pandas to RAG. You train models, build a chatbot with retrieval over your own notes, compare ChatGPT and Gemini in class, and practice the High-level AI questions used in product-company interviews.

This batch runs for 6 months. You join a live class with weekly mentor reviews. Online and Offline students follow the same syllabus, ship the same projects, and sit in the same interview lab.

Fit and outcomes

Who this is for — and where it leads

Who should join

  • Python-comfortable learners
  • Analysts moving into ML
  • Engineers targeting AI / ML / GenAI roles

Roles you can target

  • ML Engineer (junior)
  • Data Analyst + ML
  • GenAI intern / LLM app builder
Syllabus

What you will learn in 6 months

A week-by-week classroom plan. Every module ends with something you can show — a page, an API, or a demo.

1
Month 1–2 Python + data
  • pandas and SQL
  • EDA
  • Visualization
2
Month 3–4 ML & NLP
  • Classical ML
  • Model metrics
  • NLP basics
3
Month 5 GenAI
  • Prompting on ChatGPT and Gemini
  • RAG with LangChain intro
  • Evaluation
4
Month 6 MLOps + interviews
  • Simple pipeline
  • Case studies
  • High-level AI Q&A
Portfolio

Projects you ship

These go on GitHub and your resume. Mentors review the repo before demo day.

01 EDA + dashboard
02 Classification model
03 NLP notebook
04 RAG chatbot capstone (ChatGPT or Gemini)
Included

What’s in the batch

  • Python, pandas, ML models, NLP
  • RAG chatbot, prompts, ChatGPT and Gemini
  • High-level AI / ML interview bank
  • Live mentor hours and code review
  • Resume, GitHub and mock-interview support
  • Placement desk access after the project is live
How you attend

Same mentors. Pick Online or Offline.

Online

Live classroom on video. Screen-share labs, recorded recaps for missed hours, and the same weekly reviews as campus students.

Offline

Classroom + lab on campus. Pair with a batchmate, get desk-side help, and demo on a big screen at the end of the module.

Course Q&A

AI & Data Analytics interview questions

Practice the same stack you will study in class. Open any question for a model answer, then book a demo if you want to learn it live.

1 Easy ML Types AI / ML

What is supervised learning?

Short take Full answer on next page

Simple meaning

Supervised learning trains a model on labeled examples where each input already has a known target.

Open the full page for Why, Steps, Example and Key takeaway.

Read full answer Example · Mistake · Say this
2 Easy Tokens GenAI / LLM

What is a token in an LLM?

Short take Full answer on next page

Simple meaning

A token is a chunk of text the model reads and writes, often a subword rather than a full word.

Open the full page for Why, Steps, Example and Key takeaway.

Read full answer Example · Mistake · Say this
3 Easy Statistics Data Science

What is the difference between mean, median, and mode?

Short take Full answer on next page

Simple meaning

The mean is the arithmetic average, the median is the middle value after sorting, and the mode is the most frequent value.

Open the full page for Why, Steps, Example and Key takeaway.

Read full answer Example · Mistake · Say this
4 Easy MLOps Basics MLOps

What is MLOps and how is it different from regular DevOps?

Short take Full answer on next page

Simple meaning

MLOps applies DevOps ideas to machine learning so data, training code, and models can be versioned, tested, and released reliably.

Open the full page for Why, Steps, Example and Key takeaway.

Read full answer Example · Mistake · Say this
5 Easy ML Types AI / ML

What is unsupervised learning?

Short take Full answer on next page

Simple meaning

Unsupervised learning looks for structure in data that has no labels.

Open the full page for Why, Steps, Example and Key takeaway.

Read full answer Example · Mistake · Say this
See all 887 AI / ML questions GenAI / LLM questions Data Science questions MLOps questions
After the course

Opportunities after this program

Roles the placement desk is currently matching to this stack. Job placement is not guaranteed — we provide dedicated placement assistance.

Generative AI Developer Lumen Studio 1-3 years Remote · Remote 10 - 18 LPA Apply MLOps Engineer Northwind Analytics 2-5 years Bengaluru · Hybrid 12 - 20 LPA Apply Machine Learning Engineer Aether AI 1-3 years Hyderabad · Onsite 8 - 14 LPA Apply Computer Vision Intern Vertex Health Fresher Remote · Remote 20k / month Apply
View all jobs
FAQ

Before you enroll

Do I need prior coding experience?

Comfortable with basics helps, but counselors map you to the right starting week after a short call.

Where are classes held?

Offline batches run in Faridabad. Online seats cover Delhi NCR and other cities with the same syllabus and mentors.

Can I switch between Online and Offline?

Yes, if seats are open in the other mode. Tell your counselor before the next module starts so the batch roster stays correct.

When does the next batch start?

Batches open through the month. Submit enrollment with a start date — a counselor confirms your seat within 24 hours.

Is a job guaranteed after this course?

No. You get interview prep, resume support and job opportunities through the placement desk. Offers depend on your work and the hiring round.

Where do I practice interview questions?

On this page and in the interview lab for this stack. Open any question for a model answer, then book a demo if you want classroom practice.

Can I apply to jobs while I am still in the batch?

Yes. Matching roles are listed below. Prep the questions on the job page, then apply. Mentors can run a mock if you are enrolled.

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