🚀 Complete Roadmap to Become an AI Engineer
📌 Phase 1: Programming Fundamentals
Learn the foundation of programming with Python.
✅ What is Programming?
✅ What is Python?
✅ Installing Python & VS Code
✅ Variables
✅ Data Types
✅ Input & Output
✅ Type Casting
✅ Operators
✅ Conditional Statements (if, else, elif)
✅ Loops (for, while)
✅ Functions
✅ Lambda Functions
✅ Recursion
✅ Strings
✅ Lists
✅ Tuples
✅ Sets
✅ Dictionaries
✅ List & Dictionary Comprehensions
✅ Object-Oriented Programming (OOP)
✅ File Handling
✅ Exception Handling
✅ Modules & Packages
✅ Virtual Environments
✅ pip Package Manager
✅ Git & GitHub
📌 Phase 2: Python for Data
Learn how Python is used for data analysis and preprocessing.
✅ NumPy
✅ Pandas
✅ Data Cleaning
✅ Data Transformation
✅ Data Aggregation
✅ Exploratory Data Analysis (EDA)
✅ Matplotlib
✅ Seaborn
✅ Feature Engineering
📌 Phase 3: SQL
Master SQL to work with structured data.
✅ Database Fundamentals
✅ SELECT
✅ WHERE
✅ ORDER BY
✅ LIMIT
✅ Aggregate Functions
✅ GROUP BY
✅ HAVING
✅ CASE WHEN
✅ Joins
✅ Subqueries
✅ Common Table Expressions (CTEs)
✅ Window Functions
✅ Views
✅ Stored Procedures
✅ Indexes
📌 Phase 4: Mathematics
Build the mathematical foundation required for AI.
✅ Statistics
✅ Probability
✅ Linear Algebra
✅ Vectors
✅ Matrices
✅ Calculus Basics
✅ Gradient Descent
📌 Phase 5: Machine Learning
Understand how machines learn from data.
✅ Introduction to Machine Learning
✅ Types of Machine Learning
✅ Regression
✅ Classification
✅ Clustering
✅ Decision Trees
✅ Random Forest
✅ KNN
✅ Support Vector Machines (SVM)
✅ Naive Bayes
✅ XGBoost
✅ Model Evaluation
✅ Cross Validation
✅ Hyperparameter Tuning
✅ Scikit-learn
📌 Phase 6: Deep Learning
Learn neural networks and modern AI models.
✅ Neural Networks
✅ Perceptrons
✅ Activation Functions
✅ Backpropagation
✅ TensorFlow
✅ PyTorch
✅ CNN
✅ RNN
✅ LSTM
✅ Transformers
✅ Attention Mechanism
📌 Phase 7: Natural Language Processing (NLP)
Teach computers to understand human language.
✅ Text Preprocessing
✅ Tokenization
✅ Stemming
✅ Lemmatization
✅ TF-IDF
✅ Word Embeddings
✅ Word2Vec
✅ Sentence Transformers
✅ BERT
✅ Text Classification
✅ Named Entity Recognition (NER)
📌 Phase 8: Large Language Models (LLMs)
Learn how modern AI models work.
✅ What are LLMs?
✅ Tokens
✅ Context Window
✅ GPT
✅ Claude
✅ ChatGPT
✅ Llama
✅ Mistral
✅ Qwen
✅ Open-source vs Closed-source Models
✅ Temperature
✅ Top-P
✅ Top-K
📌 Phase 9: Prompt Engineering
Learn how to communicate effectively with AI.
✅ Zero-shot Prompting
✅ One-shot Prompting
✅ Few-shot Prompting
✅ Chain of Thought
✅ Role Prompting
✅ Structured Prompting
✅ JSON Output
✅ Prompt Templates
✅ Prompt Chaining
📌 Phase 10: LLM APIs
Integrate AI models into applications.
✅ OpenAI API
✅ Anthropic API
✅ ChatGPT API
✅ Hugging Face API
✅ Groq API
✅ Together AI
✅ Ollama
✅ LM Studio
✅ Function Calling
✅ Structured Outputs
📌 Phase 11: Embeddings
Learn how AI converts text into vectors.
