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AI Engineering Course

Artificial intelligence is the new thing turning the industries and skilled AI workers are becoming highly demanded. IFDA offers industry-focused AI engineering courses that prepare students for high-demand careers. It includes machine learning, natural language processing, computer vision, robots and AI ethics in an academic program that combines theory with applied training. Whether you attend our offline AI engineering courses in Delhi or enroll in an online AI engineering course near me, you’ll gain real-world skills that employers value. IFDA Institute is recognized for offering top AI courses in Delhi and is a leading AI institute in Delhi. By joining an AI course in Delhi with IFDA, students can gain practical knowledge and career-ready skills in the fast-growing field of Artificial Intelligence

Course Highlights

1.

Zero-to-production pathway

2.

Latest, industry-relevant stack and practices with real projects and a capstone.

3.

Efficient fine-tuning (PEFT/LoRA/QLoRA) and quantization for cost-effective deployment.

4.

High-throughput model serving (ONNX Runtime, NVIDIA Triton, vLLM) with simple APIs.

5.

Governance-ready workflows: documentation, basic privacy controls, and safety guardrails.

6.

Quality-by-design: experiment tracking, evaluation, drift monitoring, data-quality checks, and explainability.

7.

5 Assignments

8.

240 Hours Of Training

9.

1 Year Free Backup Classes

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Learning Outcome

Learn the concepts and practice of AI
Create and implement machine learning models
NLP, image recognition, and predictive analytics work
  Read More
Learn to use master tools, such as Python, TensorFlow and PyTorch
Get hands-on-experience in projects
Prepare to work in the field of AI engineering, data science and automation
  Read Less

Software that you will learn in this course

EXCEL
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Course Content

1)    Bridge

    1. Tool Setup
       •     Topics: CLI, VS Code, Git/GitHub, Python, Colab/Jupyter
       •     Lab: Setup repo, env, notebook
       •     Deliverable: "Hello, Data" repo + README
    2.Python + NumPy/Pandas
       •     Topics: Python basics, functions, arrays, DataFrames, I/O
       •     Lab: Clean CSV, basic stats
       •     Deliverable: Data wrangling notebook

2)    ML Foundations

   1. EDA + Viz
       •     Topics: Plots, outliers, correlation, data stories
       •     Lab: EDA report
       •     Deliverable: EDA notebook
   2. ML Math
       •     Topics: Stats, probability, gradients, loss
       •     Lab: Manual metrics, gradient step
       •     Deliverable: Math worksheet
   3. Data Prep
       •     Topics: Split, leakage, scaling, encoding, CV
       •     Lab: Sklearn pipeline
       •     Deliverable: Reusable pipeline
   4. Supervised I
       •     Topics: Linear/logistic, metrics (R², AUC, F1)
       •     Lab: House price regression
       •     Deliverable: Model table
   5. Supervised II
       •     Topics: Trees, RF, GB, feature importance
       •     Lab: Churn classifier
       •     Deliverable: Tuned model + report
   6. Unsupervised + Tracking
       •     Topics: K-Means, PCA, MLflow
       •     Lab: PCA + MLflow
       •     Deliverable: Logged runs

3)    LLMs, RAG & Agents

   1. Prompting
       •     Topics: Prompts, JSON, tools/functions
       •     Lab: Structured answers
       •     Deliverable: Prompt kit
   2. Embeddings
       •     Topics: Chunking, metadata, search, filters
       •     Lab: Index PDFs
       •     Deliverable: Vector index + queries
   3. RAG
       •     Topics: Retriever-generator, context, grounding
       •     Lab: RAG bot
       •     Deliverable: QA over docs
   4. RAG Eval
       •     Topics: Precision, rerank, hallucination
       •     Lab: Eval set + rerank
       •     Deliverable: Eval charts
   5. Agents
       •     Topics: Tools, planning, retries
       •     Lab: Tool agent
       •     Deliverable: Agent diagram + code
   6. Fine-tuning
       •     Topics: LoRA, QLoRA, 4-bit, tune vs retrieve
       •     Lab: QLoRA run
       •     Deliverable: Adapter + eval
   7. Ship App
       •     Topics: UX, limits, cost, logs
       •     Lab: Wrap RAG/agent
       •     Deliverable: Working app

4)    Deep Learning

   1. PyTorch
       •     Topics: Tensors, autograd, modules, opt
       •     Lab: Train MLP
      •     Deliverable: Loop template
   2. Training Tips
       •     Topics: Reg, LR, early stop
       •     Lab: Overfit → fix
       •     Deliverable: Training script
   3. CNNs
       •     Topics: Conv, pool, aug, vision metrics
       •     Lab: Fashion-MNIST
       •     Deliverable: Model + eval
   4. Transfer Learning
       •     Topics: Freeze, tune, checkpoints
       •     Lab: Pretrained CNN
       •     Deliverable: Model + README
   5. Transformers
       •     Topics: Tokens, emb, attn, encoder/decoder
       •     Lab: Sentiment model
       •     Deliverable: Notebook
   6. NLP Tasks
       •     Topics: Batching, masking, eval
       •     Lab: NER/text class
       •     Deliverable: Metrics dashboard
   7. Debug + AMP
       •     Topics: Speed, AMP, seeds, errors
       •     Lab: Speed vs acc
       •     Deliverable: Checklist + results

5)    MLOps

   1. API + Docker
       •     Topics: FastAPI, Docker, CI/CD
      •     Lab: Serve model
       •     Deliverable: Dockerized API
   2. ONNX
       •     Topics: Convert, latency, CPU/GPU
       •     Lab: ONNX vs native
       •     Deliverable: Bench report
   3. LLM Serving
       •     Topics: Triton, vLLM, batching
       •     Lab: Load test
       •     Deliverable: Load results
   4. Monitor + Drift
       •     Topics: MLflow, drift, quality tools
       •     Lab: Add checks
       •     Deliverable: Monitor guide

6)    Responsible AI

   1. Safety
       •     Topics: Privacy, filters, runbooks
       •     Lab: Add guardrails
       •     Deliverable: Safety list
   2. Explainability
       •     Topics: SHAP/LIME, model cards
       •     Lab: Explain + doc
       •     Deliverable: Report

7 )    Team Project

   1. Scope
       •     Topics: Problem, KPIs, sketch
       •     Deliverable: Plan
   2. MVP
       •     Topics: First build
       •     Deliverable: MVP demo.
   3. Improve
       •     Topics: Perf, monitor, fix bugs
       •     Deliverable: Perf report
   4. Deploy
       •     Topics: Final deploy, README, demo
       •     Deliverable: Live demo + repo.

Jobs and Career Opportunity After Completing Course

After completing this course you will get many job and career opportunities easily in the computer and IT field like e-commerce, government organizations, and security companies. You can start your early earnings with this course because there is no education criteria for this course and every business needs that kind of skilled employee. IFDA Institute is known for offering the best AI courses in Delhi. As a leading AI institute in Delhi, it provides practical learning, and enrolling in an AI course in Delhi will help you gain job-ready skills for a successful career.

Job profile

After completing this course

Average salary

( 1+ year experience)

AI/ML Engineer ₹3.6 L
Machine Learning Engineer ₹10–12
Data Scientist / Applied Scientist ₹12–15 L
NLP / LLM Engineer ₹10–20 L
MLOps / Model Deployment Engineer ₹10–15 L
AI Product Engineer ₹8–15 L
Data Analyst (Python/SQL) ₹4–8 L (entry-level)

Features & Facilities



Student Reviews

ifda student review
Ajay
Student
Google Review 

I recently joined the AI Engineering course at IFDA Institute, Kalkaji, and I’m really happy with my decision. The institute balances theory and practical sessions very well, and the smart classes make it easy to understand complex concepts. The course is worth the fees, and I feel it’s one of the best options for anyone looking for AI Engineering courses in Delhi.

ifda student review
Jameela
Student
Google Review 

My experience at IFDA Institute has been excellent. The faculty is supportive, and the modules are explained in a practical way. I was searching for an AI Engineering course near me, and I’m glad I chose IFDA. The AI Engineering course fees are affordable compared to the quality of training, and the smart classrooms make learning more engaging.

ifda student review
Neha
Student
Google Review 

IFDA Institute is a great choice for students interested in AI Engineering courses. The syllabus is well-structured, covering both theoretical knowledge and practical applications. The trainers are very helpful, and the fees are reasonable for the value provided. For anyone planning to start their career in AI, this institute offers one of the most reliable AI Engineering courses in Delhi.


Frequently Asked Questions

IFDA Institute offers one of the leading AI Engineering courses in Delhi with a strong focus on practical learning. Students get access to expert faculty, smart classrooms, and real-world projects. The course is structured to cover Python, machine learning, and AI concepts, helping students gain the knowledge and confidence to build a successful career.

The AI Engineering course fees at IFDA Institute are affordable compared to the quality of training provided. The institute ensures value for money by offering a well-structured syllabus, practical exposure, and smart class learning. Students not only understand the concepts but also learn industry-level skills, making the fee investment highly worthwhile for long-term career growth.

IFDA Institute provides industry-focused AI Engineering courses that blend theoretical knowledge with practical applications. The experienced faculty ensures each student learns through real-world projects and hands-on training. With smart classroom facilities and supportive mentors, students gain a strong foundation in artificial intelligence, making IFDA one of the best institutes for future-ready AI professionals.

The AI Engineering courses at IFDA are designed to build job-ready skills in Python, machine learning, data science, deep learning, and natural language processing. Students also work on real-time projects to apply concepts practically. The balanced approach of theory and practice ensures that learners not only gain technical knowledge but also become confident in solving industry-level AI challenges.

Enrolling in AI courses in Delhi helps students learn practical skills in machine learning, data science, and AI tools while building strong career opportunities in IT and related industries.

The right AI institute in Delhi should offer updated curriculum, expert trainers, and real-world projects. A well-structured AI course in Delhi can prepare you for high-demand jobs.
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