> For the complete documentation index, see [llms.txt](https://redi-school-1.gitbook.io/applicant-hub/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://redi-school-1.gitbook.io/applicant-hub/data-ai-track/python-foundations.md).

# Python Foundations

## What is the course about?

Start your journey into Data Analytics, Machine Learning, and AI with the Python Foundations course! This beginner-friendly course helps you build a strong foundation in Python programming, perfect for analyzing data and solving real-world problems.

Over 14 weeks, you’ll learn essential programming concepts, work with popular data tools like Pandas and NumPy, and explore basic visualizations to bring your data to life. By the end of the course, you’ll have practical experience, completed projects, and the confidence to continue your path in Data Analytics & AI. Join us and take the first step toward an exciting tech career! This is the beginner course of the Data Analytics & AI track.

{% hint style="info" %}

### Course Details <a href="#how-do-i-participate-in-the-courses-self-paced-mode-vs-cohort-mode" id="how-do-i-participate-in-the-courses-self-paced-mode-vs-cohort-mode"></a>

* Classes: Monday and Wednesday, 19:00 - 21:00
* Time Invest: 15 hours per week
* Timeline: Start Date is 14th of September 2026, End Date is 8th of December 2026 (14-weeks)
* Hybrid: Certain events take place in person in the following locations: NRW, Berlin, Metropolitan Region of Hamburg. [More information](#onsite-activities)
  {% endhint %}

{% embed url="<https://www.loom.com/share/88c71d9ecf644e4cba36e64a5f582a99?sid=2280d257-da86-4663-9c1d-b219c24c2972>" %}

## Why should you take this course?

* **Projects -** Apply your knowledge to a real-world data analysis project.
* **Content -** Learn syntax, operators, conditional logic, functions, and error handling, use libraries and manage code with Git & GitHub. Work with Pandas, NumPy, SQL, and create basic visualisations.
* **Your Start -** This course is the perfect starting point for your journey toward becoming a Python developer, or moving forward towards the fields of Data Analysis, Machine Learning, and AI. By the end of the course, you will have a solid foundation in Python, a GitHub portfolio showcasing your project, and a ReDI Certificate. Afterward, you can advance your skills by enrolling in the Data Analytics course.
* **Industry Experts -** The teachers are volunteers from the industry. They are experts in web development and will help you start your journey toward a tech career!&#x20;

## Learning Format

In the two weekly sessions, teachers introduce key concepts to the students and practice them with small exercises and live coding. Next to the two sessions, students are asked to apply the newly learned concepts in weekly homework and a final project.&#x20;

## Weekly Homework

Every Wednesday, students will receive homework to be submitted by Sunday evening. Homework review is part of the Monday session. There is a requirement for students to complete 80% of the homework throughout the course in order to graduate. Homework is not graded.

{% hint style="warning" %}

## **ReDI Style**

This course is about active participation. You will be asked to work independently on weekly homework to apply your newly learned skills. You are in charge of your learning journey. Are you ready to work hands-on and participate actively in the sessions? Then join us!&#x20;
{% endhint %}

## Course Outline

*The Course outline may be changed before the start.*

<table><thead><tr><th width="165">Week</th><th width="273">Topic</th><th>Content</th></tr></thead><tbody><tr><td>0</td><td>Onboarding</td><td>Get to know ReDI</td></tr><tr><td>1</td><td>Kick-Off</td><td>Teachers &#x26; Students get to know each other</td></tr><tr><td>2</td><td>Preparation</td><td>VS Code, Notebook extension, etc.</td></tr><tr><td>3</td><td>Intro to Python<br>Conditionals &#x26; Operators</td><td>Intro to Python: Input, Output, Data Types (int, str, bool, float)<br>Conditionals &#x26; Operators &#x26; Intro to functions</td></tr><tr><td>4</td><td>Flow Control</td><td>Flow control 1: lists, for/while loops, list comprehension (optional) + Functions continued</td></tr><tr><td>5</td><td>Libraries<br>IDE</td><td>Libraries &#x26; packages + date time<br>IDE Installation</td></tr><tr><td>6</td><td>Mini Project</td><td>Mini Project Intro: review tools (meeting &#x26; scheduling for peerwork)</td></tr><tr><td>7</td><td>Git</td><td>Git &#x26; GitHub Desktop</td></tr><tr><td>8</td><td>Dicts</td><td>Nested Dicts, Json Parsing, Requests and Error Handling.<br>Intro to Pandas</td></tr><tr><td>9</td><td>Pandas</td><td>Pandas</td></tr><tr><td>10</td><td>Career Week</td><td>Students can participate in a variety of career workshops.</td></tr><tr><td>11</td><td>SQL</td><td>SQL</td></tr><tr><td>12</td><td>Final Project Work</td><td>Students implement what they have learned in a final project.</td></tr><tr><td>13</td><td>Final Project Work</td><td>Students implement what they have learned in a final project.</td></tr><tr><td>14</td><td>Demo Day</td><td>Students present their final project.</td></tr></tbody></table>

## A typical week

<details>

<summary><strong>Monday 19:00 - 21:00</strong></summary>

Every Monday from 19:00 to 21:00, you have an online session in which you discuss your homework and where you will be introduced and practice new concepts.

</details>

<details>

<summary>Wednesd<strong>ay 19:00 - 21:00</strong></summary>

Every Wednesday from 19:00 to 21:00, you have an online session where the volunteer teachers introduce you to new concepts. They will share the weekly homework with you in this session.

</details>

<details>

<summary>Thursday <strong>- Monday</strong></summary>

You work on your weekly homework. That means you will be coding hands-on by yourself! If you run into problems, you can contact your class on Slack. You upload your homework before the Monday session.

</details>

## Onsite Activities

Based on your location there are different on-site activities. Find out more below.

{% tabs %}
{% tab title="Berlin" %}
If you are located in Berlin and surrounding, we invite you to some online and onsite community events throughout the semester.
{% endtab %}

{% tab title="NRW" %}
If you are located in NRW, we invite you to some online and onsite community events throughout the semester.
{% endtab %}

{% tab title="Hamburg" %}
If you are based in the Hamburg metropolitan region, you’ll attend some on-site career events and our Demo Day Celebration in December.
{% endtab %}
{% endtabs %}

## Timeline

<table><thead><tr><th width="177">Month</th><th width="230">Topics</th><th>Description</th></tr></thead><tbody><tr><td>June</td><td>Open Days</td><td>Join Info Sessions to get to know ReDI School</td></tr><tr><td>July &#x26; August</td><td>Open Days<br>Application Open<br>Student Interviews</td><td>Join Info Sessions to get to know ReDI School<br>Complete the application form and finish your prework.<br>Learners are interviewed for the course.</td></tr><tr><td>September</td><td>Kick-Off<br>Course runs</td><td>We kick-off the semester.</td></tr><tr><td>October &#x26; November</td><td>Course runs</td><td>You'll join the sessions and complete project work.</td></tr><tr><td>December</td><td>Demo Day</td><td>You'll present your final project.</td></tr></tbody></table>

## After the course

* You will have written a first program with Python, including loops, variables and functions
* You have received an introduction to Data Analytics&#x20;
* You are prepared to continue with the Data Analytics course

## How to Graduate from the Course?

To graduate and receive the ReDI Certificate, we ask you to:

* Attended 80% of the sessions (We have a [camera on policy](/applicant-hub/resources/camera-on-policy.md))
* Submit 80% of homework and a final project

{% hint style="success" %}

## Is this course for me?

* [x] you are interested in writing code and analyzing data
* [x] you can understand and speak English
* [x] you can commit at least 15 hours a week
* [x] you are eager to work on projects
* [x] you are committed to working in the [ReDI style](/applicant-hub/resources/redi-style.md)
  {% endhint %}

***

## FAQ

<details>

<summary>Not sure which track you are interested in?</summary>

If you don't have any experience with tech, apply to our introduction course: HTML & CSS, Infrastructure Basics, Python Foundations or UX/UI Design Bootcamp. To understand which tech career interests you, check out the following link:&#x20;

* [How to choose a tech career?](https://www.freecodecamp.org/news/how-to-choose-a-tech-career/)
* [Career Changer Playbook](https://ga-core.s3.amazonaws.com/cms/files/files/000/003/816/original/Career-Changers-Playbook.pdf)
* [Career Tech Guide](broken://spaces/Oa1pNW9YA7CW5ZRLDgwP/pages/5UeYVIpDeUCdYECaVbyh)

</details>

<details>

<summary>Not sure which course level to apply for? </summary>

Check out the [Prework](/applicant-hub/resources/prework.md) of the different levels. If you are a little bit challenged but able to complete a Prework, then the level is right for you.

</details>

{% hint style="info" %}

## 🤖 Unsure about which course to choose or have a question?

Try out our [AI Chatbot on Open AI](https://chatgpt.com/g/g-682b35175a5881919fac8d808d8a81ef-redi-school-dcp-course-applicants-advisor) (you need a ChatGPT account to access it). Please keep in mind that the Chatbot might make mistakes. You can find all the correct information on the Applicant Hub.&#x20;
{% endhint %}

***

### [💬](https://emojipedia.org/speech-balloon) Still unsure what to do..?&#x20;

You tried our [AI Bot](https://chatgpt.com/g/g-682b35175a5881919fac8d808d8a81ef-redi-school-dcp-course-applicants-advisor) - and didn’t find the answer you needed? Please make sure to review the **Applicant Hub** carefully, your answer is likely there. Still stuck? Check our [FAQ Page](https://redi-school-1.gitbook.io/applicant-hub/frequently-asked-questions-faq). Alternatively, you can reach out to us via email: <dcp@redi-school.org>.&#x20;


---

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