Enhanced AI Learning Roadmap 2025

By
Stephen Choo Quan
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0
54

Roadmap Flow (with Agentic AI) for 2025

01. Build Strong Foundations
02. Work with Data
03. Master Machine Learning
04. Explore Deep Learning
05. Choose AI Specialization
06. Learn Large Language Models (LLMs)
➡️ 06.5. Explore Agentic AI Systems
07. Master AI Deployment & MLOps
08. Build Real-World AI Projects
09. Transition to AI Careers

What is Agentic AI?

Agentic AI refers to intelligent agents that exhibit goal-oriented autonomy, capable of planning, reasoning, adapting, and acting with minimal human oversight.

01. Build Strong Foundations

  • Essentials:
    • Languages: Python (with Type Hints), Bash
    • Libraries: NumPy, Pandas, Matplotlib, Seaborn
    • Math: Linear Algebra (with 3Blue1Brown), Probability, Calculus
    • CS Fundamentals: Data Structures, Algorithms, Git, Docker basics

02. Work with Data

  • 📊 Data Skills:
    • Data cleaning (e.g., with Polars, Dask)
    • Exploratory Data Analysis (EDA) with Sweetviz, Pandas-Profiling
    • Use real-world datasets from Kaggle, UCI, HuggingFace Datasets
    • Basic SQL & NoSQL (MongoDB)

03. Master Machine Learning

  • 🤖 ML Concepts:
    • Classical ML: Linear/Logistic Regression, SVM, Decision Trees, Ensembles (XGBoost, LightGBM)
    • Unsupervised Learning: Clustering, PCA
    • Tools: Scikit-learn, MLflow (for experiment tracking)

04. Explore Deep Learning

  • 🧠 Neural Networks:
    • Tools: TensorFlow 2.x, PyTorch Lightning
    • CNNs, RNNs, LSTMs, GANs, Attention Mechanisms
    • Projects: Image classification, Time Series Forecasting, Style Transfer

05. Choose AI Specialization

  • 🎯 Domains to Focus:
    • NLP: Transformers, Text Summarization, Chatbots
    • Vision: Object Detection, OCR, Face Recognition
    • RL: Gymnasium, Deep Q-Learning, PPO
    • AI for Good: Climate AI, Healthcare AI

06. Learn Large Language Models (LLMs)

  • 🚀 LLM Skills:
    • Prompt Engineering (for GPT-4, Claude, Gemini)
    • Fine-tuning using PEFT / LoRA with Hugging Face
    • Tools: LangChain, LlamaIndex, OpenAI, Cohere APIs
    • Use RAG pipelines for custom chatbots

06.5. Explore Agentic AI Systems

  • Frameworks:
    • LangGraph (from LangChain)
    • CrewAI, AutoGen (Microsoft), MetaGPT
    • OpenDevin, ChatDev, AgentVerse
  • Key Concepts:
    • Tool-use (via ReAct, Toolformer)
    • Memory (short-term, long-term, vector DBs)
    • Planning (AutoGPT, BabyAGI-like models)
    • Multi-agent collaboration (task delegation, role-play)
  • Infra Tools:
    • Vector DBs: Chroma, Weaviate, Pinecone
    • Workflow orchestration: LangChain Expression Language, DAG-based graphs
  • Project Ideas:
    • Research assistant agents
    • Automated coding copilots
    • Autonomous customer service bots
    • Autonomous QA testers

07. Master AI Deployment & MLOps

  • ⚙️ Production:
    • FastAPI, Streamlit, Gradio for serving
    • Docker, Kubernetes, Airflow for orchestration
    • MLflow, Weights & Biases for monitoring
    • CI/CD & Cloud: AWS/GCP/Azure

08. Build Real-World AI Projects

  • 🛠️ Project Ideas:
    • Resume screening bot
    • Fraud detection system
    • Virtual tutor chatbot
    • Medical image diagnostic tool
    • Generative AI for art, writing, music

09. Transition to AI Careers

  • 🧑‍💼 Career Prep:
    • Build a standout portfolio on GitHub
    • Write blogs on Medium or Dev.to
    • Attend AI meetups, contribute to open-source
    • Prepare for system design & case study interviews

Bonus Enhancements

  • Use AutoML (e.g., Google Vertex AI, AutoGluon, H2O.ai) for faster prototyping.
  • Keep up with Trends:
    • Multimodal AI (text + image)
    • Edge AI with TinyML
    • Responsible AI, bias mitigation, and explainability (SHAP, LIME)

https://claude.ai/public/artifacts/9c09fca6-788a-4def-a03b-c6c62a52e062

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