1^st lesson free

Abhay

5 (5 reviews)

Rate €14
Response 6h
Students
Number of students Abhay has accompanied since arriving at Superprof
29
Number of students Abhay has accompanied since arriving at Superprof

5 (5 reviews)

€14/h

1^st lesson free

Python
Artificial Intelligence

Teaching LLMs, RAG, LangChain, FastAPI | Microsoft Certified AI Engineer | 2 Yrs Exp

Python
Artificial Intelligence

Lesson location

- online

About Abhay

I Build Production AI Systems - Not Just Jupyter Notebook Demos

Hi, I'm Abhay - an AI Engineer with 2+ years of hands-on experience building enterprise-scale AI systems that deliver real business impact:

Production based platforms → ≈₹9 Cr annual savings
ML pipeline processing 20,000+ documents monthly → 94% accuracy
LLM-powered semantic search → 12,000+ queries/month across 4 business units
RAG systems with hybrid retrieval (vector + keyword) in production

Tech Stack I Use Daily:
• LLMs: GPT-4, Claude, Gemini, open-source (Llama, Mistral)
• Frameworks: LangChain, LangGraph, LlamaIndex
• Vector DBs: Redis Stack, Pinecone, ChromaDB, Elasticsearch
• Backend: FastAPI, Redis, PostgreSQL, MongoDB
• Deployment: Docker, Kubernetes, Azure, GCP
• MLOps: MLflow, Weights & Biases, CI/CD pipelines

What Makes Me Different:

Guest Speaker at National Faculty Development Program (900+ professors & researchers)
Published AI/ML researcher (ML security, Sanskrit NLP)
Amazon ML Challenge 2023: AIR 94 out of 26,008 participants
Mentored 9 engineers → 3 converted to full-time AI roles
Conducted 100+ technical interviews for AI/ML positions
Presented work projects to Dept. of Science & Technology (Govt. of India) & Mahindra Group CTO Mohit Kapoor & Mahindra AI CEO Bhuwan Lodha

Who Should Learn From Me:

→ Professionals building AI/ML portfolios for FAANG/startup roles
→ Developers wanting to add LLM/GenAI skills (hottest market right now)
→ Engineers transitioning from traditional ML to production GenAI
→ Founders evaluating AI implementation for their products
→ Students targeting top-tier placements with cutting-edge skills

I teach what YouTube tutorials skip: deployment, scalability, cost optimization, production debugging.

B.Tech CS (8.7 CGPA) | Microsoft Azure Data Scientist | Azure AI Fundamentals | Google & IBM Data Science Certified | LeetCode Knight (Top 4.77%) | 2 years work experience building application with a cost impact of ≈₹9 Cr for an MNC.

About the lesson

Production-Ready AI/ML Training - From Fundamentals to Deployment

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TRACK 1: ML FUNDAMENTALS → JOB-READY
(12-16 weeks | Best for beginners/intermediates)

Phase 1: Python + Math for ML (3-4 weeks)
• NumPy, Pandas - data manipulation at scale
• Linear algebra, probability, statistics (applied, not theoretical)
• Matplotlib, Seaborn, Plotly - visualization
• Git/GitHub for portfolio building

Phase 2: Classical Machine Learning (4-5 weeks)
• Supervised: Linear/Logistic Regression, Decision Trees, Random Forest, XGBoost
• Unsupervised: K-Means, DBSCAN, PCA, t-SNE
• Model evaluation: Cross-validation, metrics (precision, recall, F1, AUC-ROC)
• Feature engineering & selection
• Scikit-learn mastery
• Project: End-to-end ML pipeline with real dataset

Phase 3: Deep Learning (4-5 weeks)
• Neural networks from scratch (understand backprop deeply)
• TensorFlow/Keras & PyTorch
• CNNs: Image classification, object detection, transfer learning
• RNNs/LSTMs: Time series, sequence modeling
• Transformers introduction
• Project: Computer vision or NLP model

Phase 4: Production & Deployment (3-4 weeks)
• FastAPI for model serving (REST APIs)
• Docker containerization
• Cloud deployment (Azure ML, GCP Vertex AI)
• Model monitoring & versioning
• Basic MLOps (CI/CD for ML)
• Capstone: Deploy ML app accessible via API

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TRACK 2: GENERATIVE AI & LLMs
(8-12 weeks | Assumes Python + basic ML knowledge)

**This is the HOTTEST skill in 2024-25. Companies are desperately hiring.**

Module 1: LLM Fundamentals (2 weeks)
• Transformer architecture deep-dive (attention is all you need)
• Tokenization, embeddings, context windows
• OpenAI API, Anthropic Claude, Google Gemini
• Hugging Face ecosystem (models, datasets, spaces)
• Prompt engineering: zero-shot, few-shot, chain-of-thought, ReAct
• Cost optimization (model selection, caching, batching)

Module 2: RAG - Retrieval Augmented Generation (3 weeks)
• Why RAG > fine-tuning for most use cases
• Document processing: PDF, DOCX, HTML parsing
• Chunking strategies (recursive, semantic, sentence-window)
• Embeddings: OpenAI, Cohere, open-source (Sentence-BERT)
• Vector databases: Pinecone, ChromaDB, Weaviate, FAISS
• Hybrid search: Vector + BM25/Elasticsearch
• Reranking strategies
• Evaluation: RAGAS, custom metrics
• Project: Build RAG chatbot for custom knowledge base

Module 3: LangChain & Agentic AI (3 weeks)
• LangChain components: Chains, Agents, Tools, Memory
• LangGraph for stateful multi-step workflows
• Function calling & tool use
• Multi-agent systems
• Autonomous agents (plan-and-execute patterns)
• Project: AI agent that can browse web, query databases, generate reports

Module 4: Production LLM Systems (2-4 weeks)
• FastAPI microservices architecture
• Redis/PostgreSQL for conversation memory
• Rate limiting, quota management
• Authentication (OAuth, API keys)
• Streaming responses (SSE)
• Monitoring: Token usage, latency, cost tracking
• Guardrails & safety (prompt injection prevention)
• Capstone: Production-grade AI assistant with RAG + agents

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TRACK 3: AI/ML INTERVIEW PREP
(6-8 weeks intensive)

Week 1-2: ML Theory Deep-Dive
• 100+ most-asked ML interview questions
• Math refresher: Probability, linear algebra, calculus
• Bias-variance, regularization, optimization
• Model comparison frameworks

Week 3-4: Coding for ML Roles
• Python/Pandas/NumPy challenges
• SQL for data analysis
• LeetCode patterns (arrays, trees, DP basics)
• Take-home assignment walkthroughs

Week 5-6: ML System Design
• End-to-end ML system design framework
• Case studies: Recommendation, search ranking, fraud detection, feed ranking
• Scalability, latency, cost trade-offs
• A/B testing & experimentation platforms

Week 7-8: Mock Interviews
• Live technical rounds (I've conducted 100+ real ones)
• ML debugging scenarios
• Behavioral questions (STAR method)
• Salary negotiation tactics

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WHAT'S INCLUDED:

• Live walkthroughs of my production systems (≈ ₹9Cr impact projects)
• Curated resource library (200+ papers, tutorials, GitHub repos)
• Resume + LinkedIn optimization for AI roles
• WhatsApp support (response within 24 hrs)

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TEACHING PHILOSOPHY:

• 80% hands-on coding, 20% theory
• Real messy datasets - not toy examples
• Build → Break → Debug → Understand
• Every project is portfolio-worthy & interview-ready

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Languages: English, Hindi

Recommendations

Recommendations come from relatives, friends and acquaintances of the tutor.

S

Sai

Learning from Abhay gave me real confidence in AI. He explains complex concepts simply, focuses on practical systems.
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S
Sai
Learning from Abhay gave me real confidence in AI. He explains complex concepts simply, focuses on practical systems.
S

Shivanshu

I highly recommend Abhay for programming lessons. He is patient, knowledgeable, and dedicated to helping students succeed. A trustworthy and excellent teacher!
Read more

S
Shivanshu
I highly recommend Abhay for programming lessons. He is patient, knowledgeable, and dedicated to helping students succeed. A trustworthy and excellent teacher!
A

Amit

I strongly endorse Abhay for programming classes. He is patient, well-informed, and committed to supporting students' success. His clear communication and dependable demeanor make him an outstanding instructor.
Read more

A
Amit
I strongly endorse Abhay for programming classes. He is patient, well-informed, and committed to supporting students' success. His clear communication and dependable demeanor make him an outstanding instructor.
S

Snehasis

I highly recommend Abhay as a computer programming teacher. He is knowledgeable, patient, and provides clear explanations. Abhay cares about his students’ success and creates a supportive learning environment. He is reliable, punctual, and genuinely dedicated to helping students improve. With his guidance, you can confidently build your programming skills and achieve your goals.
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S
Snehasis
I highly recommend Abhay as a computer programming teacher. He is knowledgeable, patient, and provides clear explanations. Abhay cares about his students’ success and creates a supportive learning environment. He is reliable, punctual, and genuinely dedicated to helping students improve. With his guidance, you can confidently build your programming skills and achieve your goals.
A

Amit

I highly recommend Abhay for programming classes. He is patient, knowledgeable, and dedicated to helping students succeed. His clear explanations and trustworthy nature make him an excellent teacher.
Read more

A
Amit
I highly recommend Abhay for programming classes. He is patient, knowledgeable, and dedicated to helping students succeed. His clear explanations and trustworthy nature make him an excellent teacher.
View more recommendations

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free lessons

This first lesson offered with Abhay will allow you to get to know each other and clearly specify your needs for your next lessons.

30mins

Teaching LLMs, RAG, LangChain, FastAPI | Microsoft Certified AI Engineer | 2 Yrs Exp

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