Data Science Jumpstart with 10 Projects Course is a 104-lesson 3 hours 12 minutes self-paced course by Talk Python Training. This course treats data science as a set of practical projects rather than a pile of theory.
Course facts
Lessons
104
Duration
3 hours 12 minutes
Level
All levels
Language
English
Updated
2026-09-11
Instructor
Talk Python Training
Price
Premium
This course treats data science as a set of practical projects rather than a pile of theory. You don't need prior data science experience, just a working grasp of Python, and by the end you'll have handled the same kind of problems that working data analysts and engineers face day to day.
What you'll build and practice
Loading, cleaning, and summarizing CSV and Excel data, including basic statistics
Combining and reshaping retail datasets to surface patterns hidden in raw numbers
Working with messy health data: handling missing values, spotting anomalies, and applying basic machine learning
Building predictive models around topics like air-quality trends and movie reviews
Creating interactive dashboards with Plotly and querying SQL databases directly
Throughout, the course leans on the standard Python data stack — Pandas, Matplotlib, Plotly, and friends — across 104 lessons, with the full project code available on GitHub for reference as you work.
Who teaches Data Science Jumpstart with 10 Projects Course? Talk Python Training
Talk Python Training is the paid course platform of Michael Kennedy, the host of the long-running Talk Python To Me podcast — one of the most-listened-to podcasts in the Python ecosystem. The course platform extends Michael's interview-based knowledge of the field into structured video courses taught by Michael and a curated set of guest instructors.
The course catalog covers the full Python landscape: web development with Django, Flask, FastAPI, and the broader async-Python stack; data science and pandas; LLM / RAG application development; testing and CI/CD; deployment patterns; the data-engineering side of Python; and a long list of practical Python patterns aimed at working developers. Few platforms cover the language with this much breadth from inside the Python community itself.
The CourseFlix listing under this source carries over 18 Talk Python Training courses spanning that range. Material is paid; Talk Python Training runs on per-course pricing on the original platform. Courses are aimed at developers using Python as a serious primary language rather than as a scripting tool.
What lessons are included in Data Science Jumpstart with 10 Projects Course?
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7h 30m
Frequently asked questions
What are the prerequisites for enrolling in this course?
The course assumes a basic understanding of Python programming, which is necessary for working with tools like Pandas and Pyarrow. However, no prior experience in data science is required, making it accessible for beginners who are eager to dive into the field of data science.
What types of projects will I work on during the course?
The course includes 10 projects that cover a variety of topics, such as the Retail Data Insights Project, where you will learn to combine and reshape datasets, and Health Data Deep Dives, focusing on handling missing data and foundational machine learning techniques. Other projects involve model building for Air Quality Trends and Movie Reviews, and creating interactive dashboards using Plotly.
Who is the target audience for this course?
This course is designed for individuals who are interested in starting a career in data science, data analysis, or related fields. It is suitable for beginners with some Python programming knowledge who want to learn data handling, model building, and interactive data presentation.
How does this course compare to other data science courses in terms of depth and scope?
This course provides a practical introduction to data science with a focus on real-world applications. It covers essential topics such as data handling, model building, and interactive dashboards, providing a hands-on approach with 10 projects. It may not delve as deeply into advanced topics as more specialized or longer courses but offers a solid foundation for beginners.
What specific tools and platforms will I learn to use in this course?
You will learn to use tools such as Pandas and Pyarrow for data handling, Plotly for creating interactive dashboards, and explore SQL databases. Additionally, the course covers using Jupyter and VS Code as development environments, as well as working within GitHub Codespaces.
What topics are not covered in this course?
The course does not cover advanced machine learning algorithms beyond foundational techniques, nor does it delve deeply into big data technologies or cloud computing platforms. It focuses on imparting fundamental data science skills and techniques suitable for beginners.
What is the expected time commitment for completing the course?
The course consists of 104 lessons, and while the total runtime is not specified, students should expect to spend several weeks completing the projects and exercises, depending on their familiarity with Python and ability to grasp new concepts. Dedicating regular study sessions will help in absorbing the material effectively.
