Qualification for the Job Role of a Data Analyst

Data Analyst – Focus Python

Data Analyst Course description

With the certified online course to become a Data Analyst with focus on Python, you will enter the world of data analytics. You will be able to independently clean, prepare and visualize data and make predictions relevant to your company. You will gain in-demand skills in the programming language Python and machine learning. Furthermore, you will finish the program with a final project, so that upon successful completion of the career path, you will be qualified for the job role of data analyst or another analytical role such as business intelligence analyst or financial analyst.

In this  course you will learn:  

  • Discover and filter data sources
  • Combine and prepare data professionally
  • Perform advanced data analyses independently with
  • Write simple scripts in the Python programming language
  • Make simple predictions
  • Best practices for effective data visualization
  • Play Video

    Target Audience  

    The beginner’s course is suitable for anyone who wants to learn Python as a programming language and to perform data analyses independently. You should have a basic motivation for data analytics and programming. This course is also suitable for career changers.

    Prerequisites for participation 

    No prior knowledge or programming skills are required for the course.
    Your Data Analyst course will help you to qualify for the job entry as a Data Analyst.
    Online course
    72 hours (3.5 months)
    2 modules + 1 final project
    Entry level
    German or English
    Certificate of completion
    €4,790.00
    incl. VAT
    14.02.2022
    What to Expect

    Course Overview

    Data Literacy

    Python is the #1 programming language for machine learning and data science and is relatively easy to learn, even for beginners.

    Experten­interviews

    Apply what you have learned in interactive assignments and a final project where you perform an independent data analysis with an industry data set.

    engagiertes Mentoring

    This course will qualify you directly for the job role of data analyst, as well as other analytical roles in BI, marketing or finance.

    Data Literacy

    Python is the #1 programming language for machine learning and data science and is relatively easy to learn, even for beginners.

    Experten­interviews

    Apply what you have learned in interactive assignments and a final project where you perform an independent data analysis with an industry data set.

    engagiertes Mentoring

    This course will qualify you directly for the job role of data analyst, as well as other analytical roles in BI, marketing or finance.

    Modules

    Objective:
    Introduction to programming with Python

    Description:
    Participants familiarize themselves with the interactive learning environment – the StackFuel Data Lab – and the Python programming language.

    Chapter 1 – Python Basics:
    Participants navigate through the Data Lab for the first time and get to know the basics of programming. They learn to store numbers and text as variables in Python and to store these as groups in lists. To complete these basics, participants also learn how to read error messages correctly.

    Chapter 2 – Programming Basics:
    Participants continue to build their fundamental programming skills. This chapter focuses on applying functions and, as well as conditional flow controls.

    Chapter 3 – Loops and Functions:
    The last chapter of the basics module is dedicated to flow control using loops. Participants broaden their abilities by importing additional Python packages and gain insight into code versioning with Git. By the end of the chapter, participants know the most important programming concepts that are important working as a data analyst.
    Objective:
    Independent collection, analysis and visualization of data
    with Python


    Description:
    Participants learn to access, filter, and merge new data sources.
    They practice making company data available in attractive
    visualizations tailored to the target audience, and independently
    carry out classic data processing (importing, filtering, cleaning,
    and visualizing data).


    Chapter 1 – Data Pipelines (Pandas):
    This chapter teaches the efficient use of Pandas – the standard
    data analysis tool in Python. Participants learn to use it to read,
    clean, and aggregate data in CSV files.


    Chapter 2 – Data Exploration (Matplotlib):
    Participants practice visualizing different types of data using
    marketing data. Numeric data is represented as histograms and
    scatter plots, while categorical data is represented as column
    and pie charts.


    Chapter 3 – Predictions (Statistics):
    Participants learn statistical concepts such as the median and
    quartiles using product ratings. They identify outliers and make
    simple predictions using linear and logistic regression.


    Chapter 4 – Internal Data (SQL):
    Participants learn to read databases using a human resources
    database as an example and formulate standard SQL queries.


    Chapter 5 – External Data (API):
    Participants use Python to access information such as web pages
    and APIs designed by StackFuel on the Internet.


    Chapter 6 – Advanced Jupyter:
    Participants learn Jupyter functionalities and solve advanced
    visualization problems such as live updates and interactivity in
    the context of a stock market scenario.


    Chapter 7 – Exercise Project:
    Participants analyze a New York taxi data set with over one million
    trips and use their Python skills as independently as possible to
    answer certain questions.


    Chapter 8 – Final Project:
    Participants analyze customer churn for a telecommunications
    company. They work through the entire data pipeline
    independently and answer typical questions. They then present
    their project in a 1-on-1 feedback session with the StackFuel
    mentor team

    Start dates 

    14.02.2022

    Duration: 15 Weeks

    14.03.2022

    Duration: 15 Weeks

    11.04.2022

    Duration: 15 Weeks

    01.08.2022
    Duration: 72 hours (3.5 months)
    29.08.2022
    Duration: 72 hours (3.5 months)
    03.10.2022
    Duration: 72 hours (3.5 months)

    Download the curriculum now.

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    Curriculum_DA
    LEARNING ENVIRONMENT

    Train online in your browser in our interactive learning platform.   

    StackFuel provides an innovative learning environment to develop your data skills in the most effective way – interactively and with real-world exercises. Learn to code in our Data Lab and develop algorithms and automate things with real industry datasets. Learn more now and benefit from 80% practical content in our courses. 
    WHY STACKFUEL 

    We are your strategic learning partner - including mentoring & support.   

    Whether you are an employee, a manager, or looking for a job – we will help you become a data expert with our certified and fundable upskilling and reskilling courses, which are suitable for every specialist department and every career level. We’ll ensure you learn successfully with our dedicated mentoring team to keep an eye on your progress. Our practical tasks and projects will prepare you for dealing with the latest technologies and applications.  

    Künstliche Intelligenz in Unternehmen: AI Literacy hilft Dir dabei, den Einsatz von KI in Unternehmen besser zu verstehen und Du bekommst die nötigen Kernkompetenzen, um bestehende und neue KI-Anwendungen anhand verschiedener Szenarien aus dem Business-Alltag sicher zu verstehen, für Dein Unternehmen erfolgreich zu übertragen und mit ihnen zu interagieren.
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