Data Analytics Bootcamp

Bootcamp

In phase 2 of your data analyst training, you will learn what "descriptive statistics" are all about and why they are so important for data analysts: They are especially useful when dealing with extensive data material in order not to lose the overview (and your nerves).
In addition, we will teach you how to use Google Sheets, show you some tricks to create good presentations and you will learn some helpful problem-solving methods from our coaches.

Time to set up your setup: Together we will prepare your computer to work as a hacker and finally get familiar with the command line. We will install Python in a conda environment. Now you understand the concept of "virtual environments", can create them yourself, and use package and library management tools.

You will become familiar with coding in an IDE (Integrated Development Environment), and understand Python syntax, different data types and structures, variables, loops, conditional statements and functions. And because you are now able to use and write pseudocode, you will also write your first simple program.

Now that you're deep into the topic, you'll learn about the concept of an EDA - exploratory data analysis, which examines data with little knowledge of its relationships. In the process, you'll learn how to collect, expand, and cleanse data using "pandas data frames." While performing such an EDA you already combine several data sets and deal with missing values.

Using your skills in descriptive statistics (phase 2), you extract meaning from data and learn not only what KPIs (Key Performance Indicators) are, but also create them. In addition, our coaches will teach you what makes so-called "plots" useful and how to apply them. You will use Matplotlib and Seaborn and learn how to create diagrams.

Just before the final spurt, you will learn the basics about databases and their structures with the other participants. You will learn how to use DBeaver to connect to the provided PostgreSQL database, how SQL syntax is defined and how to build an SQL query.

With the help of code-along script files and other tasks provided by the coaches, you will learn SQL execution in a practical and effective way. On top, you'll learn about the elements of data infrastructures and how to design a star schema. Sounds complicated to you? Don't worry, we'll take you through it bit by bit!

In Phase 6, you'll work with API keys to connect to APIs. We'll teach you how to automate multiple calls with different parameters. In addition, you'll learn to execute SQL queries from Python and practice reading the documentation to understand limits, request and response formats.

Heard about JSON files? We'll show you how to access them and extract data from them. With all the skills you've learned so far, you'll then run a project to solidify your knowledge. You'll do this with agile tools to organize the project as perfectly as you will later on in your job!

An important task of data analysis: Visualization. Therefore, in the last phase before the final exam, you will learn how to connect to data and perform basic data exploration - while getting familiar with the Tableau environment.
As part of this learning, you'll learn how to filter and group data, calculate fields and use parameters. LODs and table calculations will be part of your repertoire after the boot camp, as well as creating interactive dashboards.

Because we are 100% convinced that the best way to remember what you have learned is through practical application, you will spend the last four weeks of your Data Analytics Bootcamp incorporating all of your knowledge into your digital capstone project.
Once you've made it this far, you can officially call yourself a Data Analyst. Congratulations! 🙌🏼