Introduction to Data Science.

Preparation for further training as a Data Scientist

Full/Part time

German, English

The goal of the introductory course is to provide you with essential prerequisite knowledge and skills that you need for further education in data science. You will learn important mathematical basics, such as the handling of vectors, matrices and probabilities, which are necessary for the understanding of data science methods.

You will implement what you have learned with the Python programming language in connection with application scenarios in the field of data science. The training thus also serves as a test of your skills in dealing with the Python programming language.

The advanced training is suitable for you and your career aspirations if you have a degree, ideally in the fields of mathematics, computer science, natural sciences, technology, business administration, (business) information technology or have a comparable qualification or previous experience.

In this training you will learn:

Python Basics

Linear algebra

Statistical basis

Creation of structured scripts in the Python programming language
Generation of recommender systems using the Python library numpy
Recognition of the most important probability distributions

Table of contents

1
Introduction to the learning environment

Objectives:
- Getting to know and converting the most important data types
- Writing code according to the DRY principle
- Organizing and preparing data in DataFrames

Content:
- Welcome session
- Course schedule and look at building blocks
- Introduction to the learning environment
- Python basics:

Variables and data types
Functions and methods
Flow control commands
numpy arrays
Pandas DataFrames

2
Linear Algebra Part 1

Objective:
- Getting to know the basics of linear algebra

Content:
- Vectors, matrices and tensors
- Vector and matrix multiplication
- Dot product
- Metrics and norms

3
Linear Algebra Part 2

Objective:
- Calculating similarity of products using the basics of linear algebra

Content:
- Cosine similarity
- Euclidean norm
- Product recommendation based on similarity

4
Statistical Basics Part 1

Objective: Getting to know the most important discrete and continuous probability distributions

Content:

Probabilities
Discrete probability distributions:
- Binomial distribution
- Negative binomial distribution
- Poisson distribution
Continuous probability distributions:
- Uniform distribution
- Normal distribution
- Exponential distribution
Mean and standard deviation
Making predictions with distributions

5
Statistical Basics Part 2

Objective: Using Monte-Carlo algorithms for simple simulations

Content:

Law of large numbers
Central limit theorem
Monte-Carlo simulation

This training is part of the training programs:

In this training you will learn:

Python Basics

Linear algebra

Statistical basis

Creation of structured scripts in the Python programming language
Generation of recommender systems using the Python library numpy
Recognition of the most important probability distributions

Your benefits with StackFuel.

100 % Financed

Our training programs are 100% free of charge for you with an education voucher from the Federal Employment Agency.

80 % Practical content

Thanks to the high practical component, you will learn all the skills you need for everyday work in your future data job.

Flexible

Completely online and full or part-time, you can train in the way that works best for you.

Supported by mentors

Our data experts are always in contact and offer support and motivation.

Final certificate

After completing the training program, you will receive our recognized certificate to prove your skills.

Career Service included

Our Career Service supports you with advice and coaching when you start your data job.

Here's what our participants have to say:.

Over 8,000 graduates have already completed training in data and AI skills at StackFuel. Here, some of them talk about their experience:

Georges Kanaan

Participants

Data Analyst Further Training

"The training is very practical and easy to understand. I especially liked the hands-on project because it allowed me to apply what I had learned right away. The content was clearly structured and very helpful for practical application."

Shahrouz

Participants

Continuing Education for AI Professionals

"The course was well-structured, practical, and explained clearly. The hands-on exercises with Excel, Word, and PowerPoint, as well as the methods for verifying the results, were particularly helpful."

Sebastian Peter Piskalla

Participants

Continuing Education for AI Professionals

Beatrix Bauer

Junior Financial Data Engineer

Telefonica Germany

"With StackFuel, I was able to learn at a time that suits me, at my own pace and in a place where I feel comfortable."

Data Scientist Training Program

Maxi

Participant

BI Analyst Continuing Education

"The mentoring team is always available, and the schedule is flexible."

Yeonhee Kim

Participant

BI Analyst Continuing Education

"The live sessions were helpful, as was the support from the mentors."

Ninel Kloss

Participant

BI Specialist, Data Analyst, Data Scientist

"During the course, I experienced a lot of positive emotions. The learning process was perfectly organized: there was a lot of important and interesting information, as well as varied and exciting assignments. Not everything I did was always easy for me, but it was always interesting and fun. A special thank you goes to the team of mentors. Whenever you need help, they’re there—patient and professional."

Philipp Gehrlein

Participants

AI Automation Expert

"I learned a lot of new and practical things during the training that I can now apply directly in my everyday life and in a professional setting."

Marco Fischer

Data Scientist

mexxon Group

"The intensive work with important Python libraries and the concepts and mathematical basics taught were very good preparation for my new job!"

Data Scientist Training Program

Philipp Buthmann

Participants

Python Programmer

"The overall vibe was just always really great!"

Dr. Pinar Toker

Data Scientist

Eraneos Analytics

"The hands-on, real-world problems at StackFuel helped me master data analysis techniques and Python programming. The focus [...] on industry-relevant skills gave me the confidence and know-how I needed for my job search."

Data Scientist Training Program

Ulrike

Participant

Data Scientist Further Training

"I found the format very helpful because it conveys a lot of knowledge."

Amirhossein Rahimi

Data Scientist

zaplinace GmbH

"The practical, project-oriented approach makes the courses very interesting and has made my learning progress much easier."

Data Scientist Training Program

Lisa Ambrosi de Magistris Verzier

Data Analyst

Interone

"I particularly liked the well-structured curriculum and the clearly conveyed content. I now feel confident in using Python for data analysis without any previous knowledge. The dedicated career service was also a great support."

Data Analyst Training Program

Daniel Hermann

Geodata analyst

GI-CONSULT GmbH

"The competent and friendly lecturers and the examples of content made me enjoy data-driven programming. The certificates (from StackFuel) are a real plus on my CV - and the skills anyway!"

Data Scientist Training Program

Liudmila Litger

Data Analyst

Aviv Group (HomeToGo)

"I was particularly enthusiastic about the practical projects. It was as if I had already gained practical experience before my first day at work."

Data Analyst Training Program

Nurseven Simsek

Participants

BI + Data Analyst

"I really appreciated the well-structured content and the flexible organization."

Ines Bulmahn

Participant

AI & Data Transformation Manager

"The course had a very strong practical component, and I was able to take a lot away from it."

Ayu Distler

Participant

Python Programmer Training

"I was particularly enthusiastic about the practical projects. It was as if I had already gained practical experience before my first day at work."

Farbod Khiawi

Client Operations Consultant / Success Manager

AON

"What I liked best were the regular group sessions with participants and tutors. These were very exciting and beneficial for both learning and motivation."

Data Scientist Training Program

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FAQ

What sets StackFuel apart from other training providers?

Our training programs are developed and produced by our in-house team of data scientists and subject matter experts, who provide you, as a participant, with personalized mentoring throughout the course. We not only focus on realistic and practical content, but also ensure through one-on-one interaction that all your questions are answered, thereby guaranteeing your learning success. Thanks to our “learning-by-doing“ approach, you’ll learn in our interactive learning environment using realistic datasets and real-world business cases from the industry, perfectly preparing you for a successful career start in a data-related role.

Why is StackFuel the right choice for me?

With StackFuel, you’re choosing a market leader with Germany’s most innovative learning platform to develop your data skills in a hands-on way. Through certified training programs, you’ll learn online, on your own schedule, with 80 % of practical content. This will help you successfully transition into a career as a data analyst or data scientist, and you’ll learn how to apply data and the fundamentals of artificial intelligence professionally. Your new career in data starts with your online training at StackFuel.

How can AI and data skills help me launch a new career?

AI and data have become an integral part of our (professional) lives. Those who understand how to analyze data, use AI tools efficiently, and leverage AI applications possess in-demand skills for the workplace of tomorrow. That’s exactly why people with AI and data skills are particularly valuable to companies—and why new career opportunities are opening up in many industries and professional fields.

Introduction to Data Science.

In this training you will learn:

1Introduction to the learning environment

2Linear Algebra Part 1

3Linear Algebra Part 2

4Statistical Basics Part 1

5Statistical Basics Part 2

Your benefits with StackFuel.

Here's what our participants have to say:.

Get personal advice now.

FAQ

1
Introduction to the learning environment

2
Linear Algebra Part 1

3
Linear Algebra Part 2

4
Statistical Basics Part 1

5
Statistical Basics Part 2