This path is suited to learners who already have basic Python and data-analysis familiarity.
Optional preparation: Free Simplilearn Course: Data Analytics with Python, Excel and BI Tools.
About this course
Build a conceptual bridge from data science to statistical analysis, regression and machine learning with this free Google video course. Five long-form teaching chapters cover the role of data science, turning data into insights and the methods used to investigate relationships and develop models. The separate Python introduction already available on WikiFree is omitted from this selection.
What you can learn
- Data science workflow
- Data interpretation
- Statistics
- Regression analysis
- Machine learning
- Analytical reasoning
Course at a glance
| Provider | |
|---|---|
| Platform | YouTube · Grow with Google |
| Access | Free Video |
| Level | Intermediate — WikiFree audience assessment |
| Language | English |
| Selected lessons | 15 |
| Video duration | 21h 32m · allow extra time for reflection and practice |
| Details checked | 9 October 2026 |
Inside the course
Begin with the data-science overview and the chapter on translating data into insights. Continue through an extended introduction to statistics, then study regression as a way to investigate data relationships. The final chapter introduces the building blocks of machine learning. This path is suited to learners who already have basic Python and data-analysis familiarity.
Try this learning exercise
Choose a fictional prediction problem, such as estimating delivery time. Describe the outcome, possible explanatory variables, the data you would need and a sensible evaluation approach. Explain how exploratory analysis, statistical reasoning and regression would each contribute, and identify a result that would require further investigation.
How to follow the course
Choose a lesson from the list or search for a specific topic. Use Previous and Next to continue, and mark lessons complete as you go. Progress is saved in this browser without a WikiFree account.
Each course retains its relevant lessons, including videos also used in another course. Numbered series follow their original lesson or part order. Only reviewed advertisements, unrelated items and identical repeated playlist entries are excluded. Source recordings may have been made at different times.
Free access, requirements and certificates
The selected public YouTube videos are free to watch. No paid subscription, payment card or examination is required for this video learning path. WikiFree organizes the public lessons for self-paced viewing; this listing does not include a Google certificate, graded assignment or instructor feedback.
Basic Python knowledge and familiarity with tables are recommended. The videos can be watched free without running notebooks. Any practice environment or dataset is separate, and the listing does not include Google's assessed certificate program, graded projects or certification.
Official Grow with Google playlist source ↗
Use this course in a learning path
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Intermediate
Compare course focus, level and study time
| Course | Level | Focus | Study time |
|---|---|---|---|
| This course — Free Advanced Data Analytics Course: Statistics and ML | Intermediate | Data science workflow · Data interpretation · Statistics | 21h 32m of video; practice time is additional |
| Free Simplilearn Course: Data Analytics with Python, Excel and BI Tools | Beginner | Data Cleaning · Python & Excel · Insights | 698h 6m of video; practice time is additional |
| Free Data Analytics Course: Spreadsheets, SQL and R | Beginner | Frame a question and assess the quality of its data · Explore spreadsheet calculations, SQL cleaning, and R workflows · Present findings through charts, Tableau examples, and clear explanations | 18h 13m of video; practice time is additional |
| Google Cloud Data Analytics Essentials: Free Learning Instruction | Beginner | Analytics lifecycle literacy · BigQuery architecture awareness · Business-intelligence tool comparison | 2 hours; provider full-course estimate including practical activities; instruction-only study time may differ. |
| Free MIT Course: Data Analysis for Social Science | Intermediate | Lecture 03: Random Variables, Distributions, and Joint Distributions · Lecture 06: Joint, Marginal, and Conditional Distributions · Lecture 09: Expectation, Variance, and Introduction to Regression | 27h 54m of video; practice time is additional |
Provider: Google. Videos play from the Grow with Google channel on YouTube.
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