AI & Data Career Roadmap
Build from Python fundamentals through analytics, data science, machine learning, and finally generative AI — with a quick visualisation branch for fast entry.
How to read this roadmap: Start at Python. From Data Analytics you can branch into the quick Data Visualisation course, or continue the main vertical path toward Data Science, AI/ML, and GenAI.
The AI & Data course sequence
Which course comes after which. Click any course to view its full curriculum, fees and syllabus.
What AI & Machine Learning actually teaches
How the AI & Machine Learning course builds up from Python and statistics to deep learning and generative AI, stage by stage.
This is a learning outline, not a literal week-by-week schedule — tap the yellow node to see where most students start, then explore each stage's sub-topics. On desktop, dotted lines connect each stage to its topic cluster; solid lines trace the main learning path. Tap any stage below to expand its topics.
Every course in this roadmap
Python Programming
Foundation language for every AI & data track.
Data Analytics
SQL, Pandas, Tableau, Looker, GA4.
Data Visualisation
Fast-track branch: Tableau + Power BI + Looker only.
Data Science
Pandas, scikit-learn, PyTorch, MLflow, Tableau, Power BI.
AI & Machine Learning
Classical ML, deep learning, PyTorch, LangChain, RAG, LoRA.
GenAI / Prompt Engineering
Custom GPTs, RAG, fine-tuning, agentic AI.
Free demo class every Saturday
Come try before you commit. Centres in Amritsar (SRK Mall, Mall Road) and Jalandhar (65 Garha Road, Choti Baradari). ISO 9001:2015 certified, MSME registered, training since 2014.
Other career roadmaps
View all 9 roadmaps →Ready to start the AI & Data roadmap?
Free demo class every Saturday + 1:1 counselling at our Amritsar and Jalandhar centres.
Frequently asked questions
What is the fastest way into a data role?
Python (2 months) → Data Analytics (6 months) → Data Visualisation (2 months) is the quickest path to job-ready analytics/BI skills — around 10 months total.
Do I need Data Analytics before Data Science?
It is the recommended order — Data Analytics builds the SQL/Pandas/visualisation base that Data Science (with scikit-learn and PyTorch) builds on.
Is GenAI / Prompt Engineering a standalone course or does it need AI/ML first?
It is designed as a natural follow-on after AI & Machine Learning, but working professionals with basic Python can also take it directly — ask our counsellors for a fit assessment.
What tools will I actually use across this roadmap?
SQL, Pandas, Tableau, Power BI, Looker, GA4, scikit-learn, PyTorch, MLflow, LangChain, RAG pipelines, and LoRA fine-tuning — depending on which stage you reach.
Can I stop after Data Analytics and still get a job?
Yes — Data Analytics alone is a complete, hireable skillset for Data Analyst / BI Analyst roles. AI/ML and GenAI are for those targeting ML Engineer or AI Engineer roles.