Learning Plan for ML Business Analysts

Created By AI ☑ Resources Checked ☑ Fact Checked ☑ Edited ☐ Published by JDT ☐

Courses are arranged from introductory to advanced. Durations reflect Coursera’s estimates (often assuming ~10 hours/week).

1. Orientation – understanding AI’s role in business

Introductory courses to frame AI/ML in business
Course (provider) Why it matters / key skills Approx. duration
AI for Everyone DeepLearning.AI Designed for non‑technical audiences; explains what AI can and cannot do, how to spot AI opportunities, how AI projects are built, how to work with AI teams, and ethical considerations . ≈6 hours (≈1 week)
Machine Learning Essentials for Business and Technical Decision Makers AWS Discusses benefits and risks of adopting ML, identifies data & production requirements, and explains how organizations must adapt to use ML responsibly . ≈1 hour
Solve Business Problems with AI and Machine Learning CertNexus How to identify business problems for AI/ML, formulate approaches, select appropriate tools, and address data privacy & ethics . 4 modules; ≈10 hours (≈1 week)
GenAI for Business Analysts: Faster InsightsCoursera Identify specific methods & techniques for leveraging GenAI to enhance business‑process modeling, requirements gathering, and stakeholder management. 1 module; ≈2 hours
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2. Using AI‑Powered Assistants

Get hands‑on with LLMs and automation
Course Why it matters Approx. duration
Prompt Engineering for ChatGPTCoursera How to apply prompt engineering to effectively work with large language models like ChatGPT. ≈16 hours
ChatGPT: Excel at Personal Automation with GPTs, AI & Zapier Specialization Master personal automation with ChatGPT and Zapier to automate tasks, enhance productivity, and solve real‑world challenges across domains. 3 modules (≈1 module/week)
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3. Building technical foundations

Python fundamentals and core ML concepts
Course/Specialization Why it matters (key skills) Approx. duration
AI Python for BeginnersCoursera Learn Python fundamentals and how to integrate with AI tools for data manipulation, analysis, and visualization. ≈10 hours
Machine Learning SpecializationCoursera #BreakIntoAI with the ML Specialization. Master foundational AI concepts and develop practical ML skills in a beginner‑friendly, 3‑course program. 3 modules; ≈100 hours (≈10 h/week)
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4. Machine Learning Operations

From model to production
Course/Specialization Why it matters (key skills) Approx. duration
Machine Learning in ProductionCoursera Identify key components of the ML project lifecycle & pipeline; select appropriate deployment and monitoring patterns for different production scenarios. ≈10 hours
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5. More Business Analyst

Applied GenAI skills for BAs
Course/Specialization Why it matters (skills) Approx. duration
Generative AI for Business Analysts IBM Use generative AI across the BA life‑cycle for requirements, data analysis, process modeling, and communication; includes prompt‑engineering, integrating Gen‑AI tools, and adapting to evolving capabilities. ≈2 weeks
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