AI Roadmap

AI ni simple ga nerchukundam. Basics nundi AI agents varaku, practical order lo.

Creator: Augyanix · Series: AI with Augyanix · Updated with every reel

The roadmap

1. Basics first

• Computer, internet & terminal
• Git & GitHub
• Math you need (algebra, probability, statistics, linear algebra)
• Logical thinking & problem solving

2. Python

• Python basics
• Data structures
• Functions & modules
• OOP
• Files, JSON & APIs
• Virtual environments & pip
• NumPy
• Pandas
• Matplotlib
  Practice: automate small tasks with Python

3. Data science

• Data cleaning
• Exploratory analysis
• Data visualization
• SQL & databases
• Statistics for data
• Feature engineering
  Practice: analyse a dataset you downloaded

4. Machine learning

• Supervised learning (regression, classification)
• Unsupervised learning (clustering, PCA)
• Train/test split & cross-validation
• Overfitting & underfitting
• Model evaluation
• scikit-learn
  Practice: predict something from a CSV

5. Neural networks & deep learning

• Neurons & layers
• Gradient descent & backpropagation
• Activation & loss functions
• CNNs
• RNNs
• PyTorch
• GPUs & training basics
  Practice: train a small network on your laptop

6. NLP & transformers

• Text preprocessing
• Tokens & tokenization
• Embeddings
• Attention
• Transformers
• Pretrained models & Hugging Face

7. LLMs & models

• How an LLM answers (prompt lifecycle)
• Context window
• Sampling & temperature
• KV cache & streaming
• Hallucinations
• Open vs closed models
• Running models locally
  Practice: run a small model offline on your machine

8. Prompt engineering

• Prompt basics
• System prompts & roles
• Few-shot examples
• Chain-of-thought
• Structured outputs (JSON)
• Testing & improving prompts

9. Building with LLMs

• LLM APIs
• Embeddings & vector databases
• Chunking & retrieval
• RAG
• Fine-tuning basics (LoRA)
• Evaluation
• Guardrails & safety
  Practice: chat with your own documents

10. AI agents

• Tool & function calling
• Agent loops & planning
• Memory
• MCP
• Workflows & automation
• Multi-agent systems
• Agent frameworks
• Evaluation & observability
  Practice: an agent that finishes a real task for you

11. Ship it & grow

• APIs with FastAPI
• Docker basics
• Cloud deployment
• Cost & latency
• Security & privacy
• Responsible AI
• Portfolio projects
• Reading papers & staying updated

+ And more

AI fast ga marutundi. Kotha concepts vachinappudalla add chestham.

Learn it offline too

• Python, Jupyter notebooks, datasets download chesukoni laptop lo practice cheyandi
• Small open models ni local ga run cheyandi
• Prati phase ki oka chinna project cheyandi
• Notes paper meeda rayandi, concept ni friend ki cheppandi

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