Short answer
As a complete beginner you should start with applied generative AI, not machine learning theory. Learn what AI and generative AI are, get fluent with two or three AI assistants, learn to structure prompts so output is reliable, then immediately apply it to work you already do — writing, research, planning, reporting or design. Coding and mathematics are not required for this path. Once you can produce real output with AI, the natural next step is automation: connecting your data, AI and everyday tools into workflows that run repeatedly.
By Chandan Maheshwari, AI mentor & consultant, founder of School of AI · Last updated
A sensible first 90 days
Order matters more than volume.
- Weeks 1–2: understand AI, generative AI, agents and automation as concepts
- Weeks 3–4: pick two AI assistants and use them daily on real tasks
- Weeks 5–8: build reusable prompt structures instead of one-off prompting
- Weeks 9–12: produce something real — a report system, content system, site or SOP set
What beginners should skip at first
Skip model training, Python for machine learning, maths refreshers and tool-hopping. None of them make you more capable in your actual work in the first three months, and all of them cause people to quit.
Do I need coding or maths?
No. The GenAI Foundation Program is explicitly no-coding practical application. Engineering background is not a prerequisite.
Why a mentor shortens this
Beginners rarely fail on information — they fail on judgement: which tool, which task, how good is good enough. Live mentor-led sessions answer that against your own work, which is why School of AI runs live cohorts rather than a recorded library.
Learning this with School of AI
GenAI Foundation Program
Live, mentor-led and online, open to learners in India and abroad.
Indian residents · INR
₹16,900 + 18% GST
Regular fee ₹19,999
Total: ₹19,942 (incl. 18% GST)
Non-Indian residents · USD
$249 USD