Data Science Jumpstart with 10 Projects Course

This course is carbon neutral.

Course Summary

Unlock the Power of Data with Python.

What students are saying

Highly recommended, very nice flow of concepts, modern dev tools, and packs a lot of content into a short space.
-- Alan

What's this course about and how is it different?

This course will empower you with the skills and tools to dive deep into data science using Python. We assume you have a foundational understanding of Python but not data science concepts. This course exposes you to the same tools that data scientists, data engineers, analysts use data to tackle real-world challenges.

In this course, you will:

  • Delve into loading, cleaning, summarizing, and basic statistics with both CSV and Excel data.
  • Master the art of combining and reshaping datasets to uncover hidden patterns in the Retail Data Insights project.
  • Understand missing data handling, abnormal data recognition, and foundational machine learning techniques through Health Data Deep Dives.
  • Create models to explore Air Quality Trends & Movie Reviews.
  • Construct interactive dashboards using Plotly and explore SQL databases in the Interactive Dashboards & SQL Exploration section.
  • Harness powerful libraries such as Pandas, Matplotlib, Plotly, and more.

Transform from a data enthusiast to a Data Hero!

View the full course outline.

Who is this course for?

For anyone passionate about unveiling data insights using Python. Whether you are a beginner just starting with data science or an intermediate learner aiming to solidify your understanding and get exposure to more libraries, this course has something for everyone.

Follow along with subtitles and transcripts

Each course comes with subtitles and full transcripts. The transcripts are available as a separate searchable page for each lecture. They also are available in course-wide search results to help you find just the right lecture.

Each course has subtitles available in the video player.

Get hands-on for almost every chapter

The best way to learn new data tooling techniques or library features is to try them out. Every key concept in this course comes with a practical section where you can dive in and get your hands dirty. Not just understanding the theory, but actually applying it, helps you get a true feel for the tools and techniques, and you'll begin to see how you can integrate them into your own data projects.

These hands-on exercises typically range from 10 to 20 minutes, ensuring you get immediate practice on what you've learned without it becoming too time-consuming.

github.com/talkpython/data-science-jumpstart-with-10-projects-course


Who am I? Why should you take my course?

Who is Matt Harrison?

Who is Matt Harrison? I'm Matt. Thanks for dropping by. My friend Michael asked me to prepare a class to explain the cool new features in Python 3. There are a couple of reasons I'm especially qualified to teach you Python.

I've been using Python professionally since 2000 across a broad domain of areas. I ran the local Python group five years. Helping to mentor newbies and connect them with others in the industry.

I've been training and teaching for a long time. I've taught at large companies, small companies, universities, and many conferences. I've given courses for elementary students on programming drones with Python, and have taught retired professionals to program in Python.

I'm a best selling Python author. My most recent book Illustrated Guide to Python 3 has been a best seller on Amazon, as have my Learning the Pandas Library and my Treading on Python series.

Students like my training. I focus on the practical application. Below are some quotes from recent students.

"The hands-on activities were a great learning tool. Matt presented the material very well and did a great job of interacting with students and answering their questions and concerns. The material was perfect for learning new things with Python 3 and OOP!" - Jennifer S.
"Good overview of Python and showed a range of commands. Covered many aspects of the language and you were left with a sense of the capabilities." - Sam V.
"Matt's experience with Python and his ability to deal with those fundamental getting started problems. He demonstrated a way to get started, without getting bogged down by the overwhelming complexity and potential of Python." - Jake R.
"Matt obviously had an in-depth knowledge of Python and did a terrific job of explaining the material he presented. Questions were clearly answered and explanations of the code were easy to follow. Basing the course on the Markov Chain example was exceptionally well done. The example hits on many concepts that are important to an experienced programmer, with the code still being accessible to an entry-level programmer." - Anna O.

Free office hours keep you from getting stuck

One of the challenges of self-paced online learning is getting stuck. It can be hard to get the help you need to get unstuck.

That's why at Talk Python Training, we offer live, online office hours. You drop in and join a group of fellow students to chat about your course progress and see solutions via screen sharing.

Just visit your account page to see the upcoming office hour schedule.

The time to act is now

Take advantage of the Python data libraries today. You will use the same tools that professionals use and learn how to handle data with these 10 projects.

Course Outline: Chapters and Lectures

8:14
0:51
2:00
1:37
2:09
1:10
0:27
31:58
0:34
5:25
6:34
5:36
4:49
8:36
0:24
14:38
0:42
1:45
1:31
3:02
2:07
3:33
1:48
0:10
11:56
0:14
0:57
1:33
2:51
2:36
2:19
0:56
0:30
24:06
0:38
0:33
0:49
3:48
2:43
6:05
3:35
5:30
0:25
23:26
0:37
0:46
2:46
0:43
1:17
0:49
2:25
3:07
1:05
1:27
0:14
0:14
0:22
0:19
0:17
0:38
1:07
0:49
4:18
0:06
21:52
0:31
0:51
0:52
2:03
2:36
0:52
0:57
1:29
3:23
3:26
2:30
1:45
0:16
0:21
11:37
0:25
1:31
0:55
2:43
1:43
2:40
1:40
20:16
0:21
2:00
5:00
4:58
6:01
1:47
0:09
8:48
0:13
1:32
0:55
0:31
1:19
1:57
1:54
0:27
13:26
0:10
0:22
1:44
2:01
2:28
3:40
1:43
1:10
0:08
1:16
1:16
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