What you will be able to do
- Write clean Python for data cleaning, analysis and automation
- Query relational data confidently with SQL joins, windows and aggregations
- Explain and apply core statistics: distributions, sampling, hypothesis tests
- Train, evaluate and tune supervised machine learning models
- Ship three portfolio projects with clear write-ups and reproducible notebooks
Before you start
- Comfort with school-level algebra
- A laptop with Python 3 and a code editor installed
- No prior programming experience required
The week-by-week plan
Already know an early week? Start at your first real gap instead of week one — the projects still build on each other from wherever you join.
Week 1: Python foundations
- Variables, types and control flow
- Functions and modules
- Lists, dicts and comprehensions
- Reading files and CSVs
Project: Command-line script that summarises a CSV of student marks
Week 2: NumPy and vectorised thinking
- Arrays and dtypes
- Broadcasting
- Aggregations and axes
- Random sampling
Project: Simulate 10,000 dice rolls and chart the distribution
Week 3: pandas for real data
- Series and DataFrames
- Indexing and filtering
- Missing values
- Group-by and merges
Project: Clean a messy public dataset and publish the cleaning notebook
Week 4: Exploratory data analysis
- Descriptive statistics
- Matplotlib and seaborn
- Outlier detection
- Correlation vs causation
Project: Full EDA report on a city housing dataset
Week 5: SQL for analysts
- SELECT, WHERE, ORDER BY
- Joins across tables
- Aggregations and HAVING
- Window functions
Project: Answer ten business questions against a sample e-commerce database
Week 6: Statistics that matter
- Probability basics
- Normal and binomial distributions
- Confidence intervals
- A/B testing and p-values
Project: Design and analyse a simulated A/B test
Week 7: Supervised learning: regression
- Train/test split
- Linear and polynomial regression
- Loss functions
- Overfitting and regularisation
Project: Predict house prices and document error analysis
Week 8: Supervised learning: classification
- Logistic regression
- Decision trees
- Precision, recall, F1
- Confusion matrices
Project: Build a churn classifier with a calibrated threshold
Week 9: Feature engineering and pipelines
- Encoding categoricals
- Scaling and imputation
- scikit-learn pipelines
- Cross-validation
Project: Refactor week 8's model into a reproducible pipeline
Week 10: Ensembles and tuning
- Random forests
- Gradient boosting
- Hyperparameter search
- Feature importance
Project: Enter a beginner Kaggle competition and log your score
Week 11: Communicating results
- Storytelling with charts
- Dashboards
- Writing an analysis README
- Stakeholder summaries
Project: Turn your best model into a one-page decision brief
Week 12: Portfolio and interviews
- Cleaning up repositories
- Case-study write-ups
- SQL interview drills
- Statistics interview drills
Project: Publish a portfolio site linking three finished projects
Tools you will use
Where this roadmap leads
Data Analyst
Strongest match after week 6 — SQL plus EDA covers most entry job descriptions.
Junior Data Scientist
Reachable after week 12 if all three portfolio projects are complete.
Business Intelligence Analyst
Add a dashboard tool such as Power BI or Metabase to weeks 11-12.
Frequently asked questions
How long does it take to learn data science?
With 8-10 focused hours a week, this roadmap takes about 12 weeks to reach interview-ready fundamentals. Part-time learners at 4 hours a week should plan for roughly six months.
Do I need a maths degree for data science?
No. You need comfortable school-level algebra plus the applied statistics in weeks 4 and 6. Deeper linear algebra and calculus only become important if you move into research or deep learning.
Should I learn Python or R first?
Python. It covers analysis, machine learning and production code with one language, and most Indian and global job listings ask for it.
Are certificates enough to get hired?
Rarely on their own. Hiring managers respond to three finished projects with clear write-ups far more than to course certificates, which is why every week here ends in something you build.
Want this plan scheduled for you?
Pathlix turns roadmaps like this into daily goals sized to your study hours, tracks your streak, and tests you every week.