Data Scientist
A data scientist builds models and analyses that predict, explain and guide decisions.
- Explore data and form hypotheses
- Engineer features and train models
- Evaluate models honestly
- Communicate results and limits
- An end-to-end ML project in Python
- Model evaluation with the right metrics
- An analysis write-up
Where it leads: Senior data scientist, ML engineer, or research roles.
Every skill, at the level the job needs
Updating… · change the level or company to see how it shifts
machine-learning
core- Data structures
- Exceptions
- Exception handling
- Functions
- Declaring functions
- If statement
python
core- Type casting
- Basic Syntax
- Exceptions
- Exception handling
- Basic data types
- Variables
git-github
core- git init
- What is Version Control?
- Why use Version Control?
- git config
- Local vs Global Config
- Git
ai-data-scientist
core- Mathematics
- Statistics
- Descriptive statistics
- Econometrics
- Coding
- Exploratory Data Analysis
datastructures-and-algorithms
core- Language Syntax
- Control Structures
- Python
- Pseudocode
- Pseudocode basics
- Functions
What the levels mean
- L1 · AwareKnows what it is and when it's used
- L2 · BasicsCan use it with guidance
- L3 · WorkingUses it independently on the job
- L4 · StrongHandles hard cases, reviews others
- L5 · ExpertDesigns with it, teaches it
Interviews, by kind of company
Your route adds an interview track that matches the company you choose.
Large IT services firms: aptitude, fundamentals, technical and HR rounds.
Online assessment, coding rounds, a design round.
Hard timed coding rounds, system design, behavioural interviews.
Questions
What does a Data Scientist need to know?
AI and Data Scientist Roadmap, Machine Learning, Python Developer at a working level, plus SQL Roadmap. The skills section above lists every one with its level.
How long does it take to become a Data Scientist?
About 137 hours of study from scratch. At 10 hours a week that's roughly 14 weeks; anything you already know is skipped after the readiness test.
I already know some of this. Do I start from zero?
No. The optional readiness test finds what you already know and your route skips it.
Does the route change for product companies or senior roles?
Yes. Choose your level and the kind of company above: the skills and target levels adjust, for example deeper data structures and system design for product companies.
Other roles in the Data & AI track
They share many skills with this one, so progress carries over if you switch.
Answer questions with SQL, Python and dashboards.
Pipelines and data platforms.
Applications built on AI models: assistants, agents, AI features.
Deploy and run machine-learning systems in production.