The Knowledge House · Innovation Fellowship

Data Analytics Track

Data Analytics track

Show tools

In Phase 1 (Feb–May) you'll build a programming and statistics foundation using Python, Git, and Pandas; in Phase 2 (June–Aug) you'll move into SQL at scale, dashboarding, and a full progression through regression, classification, ensemble methods, and neural networks.

Phase 1 tools

Tool	Why you need it	Link	Cost
Anaconda	Manages your Python environment and packages — set this up in week two of the program.	anaconda.com/download	Free
Jupyter Notebook	Where you'll write and run a lot of your early Python and data analysis work.	jupyter.org/install	Free
Replit	An in-browser alternative for running Python, introduced alongside Jupyter early on.	replit.com	Freemium Free tier available.
NumPy	Numerical computing fundamentals used throughout the data analysis coursework.	numpy.org/install	Free
Pandas	Central to the track — indexing, dataframe manipulation, group analysis, and time-series work all build on this.	pandas.pydata.org/getting_started.html	Free
Requests (Python library)	Used for working with REST APIs and unstructured data.	requests.readthedocs.io	Free
Google Sheets	Used for multivariate data analysis exercises.	sheets.google.com	Free

Phase 2 tools

Tool	Why you need it	Link	Cost
Google BigQuery	You'll query a real Amazon retail dataset through BigQuery as a graded project.	cloud.google.com/bigquery	Freemium Free tier available (BigQuery sandbox), paid usage-based tiers beyond that.
Tableau	Where you'll build reporting and monitoring dashboards using business-intelligence best practices.	tableau.com	Paid only Free trial; paid product (student/education licensing may be available — worth checking with your instructor).
scikit-learn	Used across the regression, classification, and ensemble-method curriculum (logistic regression, decision trees, KNN, Naive Bayes, Random Forest).	scikit-learn.org	Free
XGBoost	Covered specifically during the ensemble-methods unit.	xgboost.readthedocs.io	Free
Keras	Introduced for neural networks, multi-layer perceptrons, and an MNIST handwritten-digit recognition project.	keras.io	Free
GitHub Codespaces	Your Phase 2 development environment runs through this — a cloud-based VS Code environment tied to your GitHub repo.	github.com/features/codespaces	Freemium Free tier included with GitHub account; paid usage beyond free monthly hours.