✅ Artificial Intelligence Engineer Roadmap 🤖🧠

🚀 Foundations
- Mathematics
• Linear Algebra, Calculus
• Probability & Statistics
- Programming
• Python (core language)
• C++ (for performance)
• SQL (for data handling)
- Computer Science Basics
• Data Structures & Algorithms
• OOP Concepts

📘 Core AI Concepts
- Search Algorithms
• BFS, DFS, A*
- Knowledge Representation
• Ontologies, Graphs
- Logic & Reasoning
• Propositional & Predicate Logic
- Planning & Decision Making
• Markov Decision Process (MDP)
• Game Theory Basics

🧠 Machine Learning & Deep Learning
- ML Algorithms
• Regression, Classification, Clustering
- Deep Learning
• Neural Networks, CNN, RNN
• Transformers, Attention Mechanisms
- Frameworks
• TensorFlow, PyTorch, Keras

📊 NLP & Computer Vision
- NLP
• Tokenization, Lemmatization
• Language Models (BERT, )
- CV
• Image Classification, Object Detection
• OpenCV, YOLO, Mask R-CNN

🛠 Tools & Platforms
- Jupyter, GitHub, Docker
- MLflow, Weights & Biases
- Hugging Face, OpenAI APIs

☁️ Model Deployment & Monitoring
- FastAPI, Flask for APIs
- CI/CD Pipelines
- Cloud (AWS Sagemaker, GCP Vertex AI, Azure ML)

🧑‍💼 Real-World Essentials
- AI Product Thinking
- Explainable AI (XAI)
- Ethics, Bias & Fairness
- Working with Stakeholders

📚 Learn From
- Papers with Code
- Arxiv.org
- DeepLearning.AI
- Kaggle Projects
- YouTube Lectures (e.g. MIT, Stanford)

👍 Tap ❤️ for more!

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