Become an AI Engineer 🚀

The only roadmap you needed to understand this topic in deep dive
Understand AI end-to-end -> Build production-grade AI systems -> Ace interviews at any company
with love from Diginode ❤️

Prerequisites & Fundamentals

Programming: Python, JavaScript/TypeScript

Linear Algebra (Matrix Ops, Eigenvalues)

Calculus (Derivatives, Gradients)

Probability & Statistics

Data Structures & Algorithms

Version Control: Git & GitHub

APIs and Web Basics (REST, JSON)

Machine Learning (ML) Foundations

Supervised vs Unsupervised Learning

Regression, Classification, Clustering

Decision Trees, SVMs, k-NN

Model Evaluation Metrics (Precision, Recall, AUC, F1)

Cross-validation, Regularization

Model Deployment (ONNX, TensorFlow Lite, TorchServe)

Deep Learning

Neural Networks (ANN, CNN, RNN, LSTM, GRU)

PyTorch / TensorFlow / Keras

Backpropagation

Optimizers (SGD, Adam)

Transfer Learning

Computer Vision & NLP basics

Autoencoders, GANs

LLMs & Transformer Architectures

Transformer Basics (Attention, Positional Encoding)

GPT, BERT, LLaMA, Claude, Gemini

Context Length, Capabilities

Inference vs Training

Fine-tuning & LoRA

Token Management & Pricing

Instruction Tuning vs Pretraining

Prompt Engineering (PE)

Zero-shot, Few-shot Prompting

ReAct, Chain-of-Thought

Constraints & Validation

Tool use with OpenAI Functions

Assistant API, Manual chaining

Vector Embeddings & Search

Embedding Models (OpenAI, Hugging Face, BAAI/bge)

Semantic Search, Similarity Search

Use Cases: Recommender Systems, Classification, Retrieval

Vector DBs: FAISS, Pinecone, Weaviate, Qdrant, LanceDB

Retrieval-Augmented Generation (RAG)

RAG vs Fine-Tuning

Chunking, Indexing, Embedding

Vector Retrieval

Tools: LangChain, LlamaIndex, Assistant API

Hybrid RAG, Multi-hop RAG

AI Agents

What Are Agents?

Tools: LangChain Agents, ReAct + Functions, AutoGPT

Memory, Tool usage, Planning

Deployment of Agent Workflows

Multimodal AI

Vision: Image Understanding (CLIP), DALL·E, Midjourney

Audio: Whisper, TTS, STT

Video: Captioning, Transcription

Tools: Hugging Face, LangChain Vision, LlamaIndex, OpenAI Vision API

Open Source Models & Ecosystem

Model Hubs: Hugging Face, Ollama, GPT4All

Run LLMs Locally: Ollama, LM Studio

Inference SDKs, Transformers.js

Community Models: Mistral, LLaMA, Falcon, etc.

AI Ethics & Safety

Prompt Injection

Adversarial Attacks

Moderation APIs

Bias, Fairness, Privacy

Secure Deployment Practices

MLOps & AI Deployment

Model Serving (FastAPI, Flask, Streamlit, Gradio)

Deployment Platforms: AWS, GCP, Azure, Vercel

CI/CD for AI

Monitoring & Logging

Tools: MLflow, Weights & Biases, Docker, Kubernetes

Tooling Ecosystem

AI IDEs: Cursor, VSCode AI extensions

Code Completion: GitHub Copilot, Tabnine

LangChain, LlamaIndex, Haystack

Jupyter, Colab, Kaggle

Product Thinking for AI Engineers

Understand User Usecases

Design AI Features into Products

Consider UX, Latency, Privacy

A/B Testing, Impact Metrics

Congratulations 🎉

Thank you for following this roadmap. You’ve made tremendous progress, and your hard work is truly commendable. Feel free to share it with your friends if you found it helpful!.If you believe in yourself and keep pushing forward, success is inevitable.

“The journey of a thousand miles begins with a single step.”