Data Analytics

Python

• Basic and composite built-in data types

• DataFrames and Series

• Groupby and aggregation

• String processing and regex

• Joins & concat/unions

Data Analysis

• Missing values

• Statistics for summarizing data

• A/B Testing

Visualization

• Types of Plots

• Intro to Matplotlib and Seaborn

• Data Storytelling

SQL, Databases and Modern Data Stack

• Learn SQL

• Databases

• Analyze data with Tableau, Looker

• Learn the modern data stack which is used in industry

• Job Readiness: Soft skills through career trainings geared towards preparing you for job applications & interviews, networking events and job fairs.

• You will learn from experts in the industry to start a career in tech.

• you are motivated to learn about Data Analytics

• you are able to understand and speak English

• you have a good understanding of Python

• you can commit at least 10 hours a week (classes + self-study)

You can prepare yourself for this course by completing the following material.

1. Complete the Preparation Material Google Colab

   1. Please create a copy of the Prep Material Google Colab

   2. Complete the Challenge

   3. You find supportive resources and material in the Colab if you want to deepen your knowledge of the concepts.

2. Learn more about the job market: Data Science, Data Analyst vs Engineer, Differences in Job Titles.

• you have built your own Data Analytics project (ML or data analysis)

• you know how to start analyzing a dataset

• you know about Data Science Tools (pandas, sklearn, ...);

• you can continue learning with our Data Analytics alumni group

• you can start looking for internships and junior positions

You have two sessions per week. One is taking place online, the other one on-site.

• Mondays: Online Session

• Wednesdays: On-site at the Factory Görlitzer Park, Berlin

Homework, group projects and your personal study takes place online. It is important that you can attend both sessions per week. You cannot take this course purely online.

• Career & Soft Skills Workshops, Company Visits

• ReDI Mentorship Program (mentors in the IT industry)

• ReDI Talent Pool (job listing platform)

• SkillBuild self-paced eLearning (by IBM & ReDI)

• You should expect to spend a minimum of 8 hours for career workshops or trainings during the semester.