🚀 AI Architect Roadmap

Overview:
This repository documents my 25-day journey to build essential skills for an AI Consultant role. Each day is captured in a dedicated Jupyter Notebook that covers key topics—from AI architecture and machine learning fundamentals to MLOps, cloud deployments, and ethical AI practices.

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📑 Table of Contents

• Overview
• Progress Tracker
• Daily Topics
• Tech Stack
• Usage Instructions
• Contact

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📊 Progress Tracker

Day	Topic	Notebook Filename
1	AI Architecture Fundamentals	Day01_AI_Architecture_Fundamentals.ipynb
2	Data Layer & Pipelines	Day02_Data_Pipelines.ipynb
3	Model Training & Processing	Day03_Model_Training.ipynb
4	Introduction to LLMs & Generative AI	Day04_LLMs_GenerativeAI.ipynb
5	Retrieval-Augmented Generation (RAG)	Day05_RAG_Chatbot_Architecture.ipynb
6	Prompt Engineering	Day06_Prompt_Engineering.ipynb
7	Overview of Cloud AI Platforms	Day07_Cloud_AI_Platforms.ipynb
8	Cloud Deployment Strategies	Day08_Cloud_Deployment_Strategies.ipynb
9	MLOps & CI/CD Pipelines	Day09_MLOps_CICD.ipynb
10	Containerization & Orchestration	Day10_Docker_Kubernetes.ipynb
11	Data Engineering for AI	Day11_Data_Engineering.ipynb
12	Advanced Model Deployment	Day12_Advanced_Deployment.ipynb
13	Responsible AI & Ethics	Day13_Responsible_AI.ipynb
14	AI Security & Adversarial Attacks	Day14_AI_Security.ipynb
15	AI Governance & Monitoring	Day15_AI_Governance.ipynb
16	AI Consulting Case Studies	Day16_Case_Studies.ipynb
17	Estimating AI Project Costs & ROI	Day17_Cost_ROI.ipynb
18	Advanced LLMOps	Day18_LLMOps.ipynb
19	Business Transformation & AI Strategy	Day19_AI_Strategy.ipynb
20	Communication & Presentation for Consulting	Day20_Communication.ipynb
21	Building an AI Portfolio	Day21_Portfolio.ipynb
22	Emerging Trends in AI	Day22_Emerging_Trends.ipynb
23	Mini Project – Part 1	Day23_MiniProject_Part1.ipynb
24	Mini Project – Part 2	Day24_MiniProject_Part2.ipynb
25	Review, Reflection & Next Steps	Day25_Review_Reflection.ipynb

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🗓 Daily Topics

Each notebook contains:

• 📚 Theory & Background: Detailed markdown notes covering key concepts.
• 💻 Hands-On Coding: Python code examples, experiments, and simulations.
• 📈 Diagrams & Flowcharts: Text-based diagrams to visualize architectures and workflows.
• 📝 Analysis & Reflections: Key takeaways, best practices, and next-step insights.
• 📋 Commit Log: A summary of daily learnings to track progress over time.

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🛠 Tech Stack

• Languages & Frameworks: Python, TensorFlow, PyTorch, scikit-learn
• APIs & Libraries: LangChain, OpenAI API, Hugging Face Transformers
• Web & Deployment: Streamlit, FastAPI, Flask
• Cloud Platforms: AWS SageMaker, Azure ML, Google Vertex AI
• Containerization & Orchestration: Docker, Kubernetes
• MLOps Tools: MLflow, GitHub Actions

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⚙️ Usage Instructions

1. Clone the Repository:

   git clone https://github.com/yourusername/AI-Consultant-Roadmap.git

2. Navigate to the Directory:

   cd AI-Consultant-Roadmap

3. Launch Jupyter Notebook:

   jupyter notebook

   Open and follow the notebooks to progress through the 25-day learning plan.

4. Track Your Progress:
   Commit and push updates as you complete each day's notebook to document your learning journey.

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📬 Contact

For questions, collaboration, or feedback, please reach out:

• Email: sayande01@gmail.com
• GitHub: Sayande01

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Happy Learning & Building!
Sayan De

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