🎯 Minimalist AI/ML Learning Plan for Principal Software Engineers & Architects

This curated list focuses on essential AI/ML knowledge to help you architect, lead, and guide AI/ML initiatives, without going deep into model-building.

---

🧠 1. Understand AI at a Strategic Level

✅ AI for Everyone – Andrew Ng (Coursera)

• Platform: Coursera
• Duration: ~6 hours
• Focus: Strategic and non-technical understanding of AI
• Why: Learn how to scope AI projects, talk to ML teams, and understand AI's business value.

---

🔍 2. Learn the Core of Machine Learning

✅ Supervised Machine Learning: Regression and Classification – Course 1

• Platform: Coursera (Part of Andrew Ng's ML Specialization)
• Duration: ~15 hours
• Focus: Practical understanding of how ML models are trained and evaluated
• Why: Enough to grasp ML fundamentals, useful when discussing solutions with ML teams.

---

⚙️ 3. Understand MLOps and ML System Architecture

✅ Machine Learning Engineering for Production (MLOps) – DeepLearning.AI

• Platform: Coursera / DeepLearning.AI
• Duration: ~4 weeks part-time (4 courses)
• Focus: ML lifecycle, pipelines, CI/CD for ML, monitoring, and scaling
• Why: Learn how real-world ML systems are designed, deployed, and maintained.

---

🤖 4. Apply Generative AI in Software Engineering

✅ Generative AI for Software Engineers – DeepLearning.AI

• Platform: DeepLearning.AI
• Duration: ~6 hours
• Focus: Using LLMs like GPT in software workflows and applications
• Why: Understand prompt engineering, chaining, and integration of LLMs in software systems.

---

🛡️ 5. Build Ethically Responsible AI Solutions

✅ Responsible AI – Microsoft Learn

• Platform: Microsoft Learn
• Duration: ~4–6 hours
• Focus: Fairness, bias, transparency, explainability, data governance
• Why: Crucial for enterprise-level leadership and responsible tech decisions.

---

📘 Summary Table

Area	Course	Platform	Duration
AI Strategy	AI for Everyone	Coursera	~6 hrs
ML Fundamentals	Supervised ML (Course 1)	Coursera	~15 hrs
ML Systems & MLOps	MLOps Specialization	Coursera/DeepLearning.AI	~20 hrs
GenAI in Software	Generative AI for SWE	DeepLearning.AI	~6 hrs
Responsible AI	Responsible AI	Microsoft Learn	~4–6 hrs

---

📝 Tip

You can complete this plan over 6–8 weeks at 3–4 hours/week and be well-positioned to:

• Evaluate ML proposals
• Architect systems with ML components
• Lead responsible AI initiatives
• Stay relevant in the era of GenAI