Data Science Course | Constructor Learning

Program overview

Recent graduate, entrepreneur, or you want to expand your existing skill set? In any case, our Bootcamp is exactly what you are looking for. We have carefully designed our curriculum to contain the most up-to-date tools currently in demand in the job market. This is what makes our Data Science Bootcamp innovative and what will enable you to take the next step in your career.

Awarded as one of the best Data Science bootcamps worldwide

Constructor Learning's Data Science bootcamp has been recognized as one of the best in the world.

Upcoming dates

Zurich

Munich

Bremen

Remote

You need to select a location to see upcoming dates and prices.

Students say

Lingxuan Zhang

Data Science

❝"I decided to research some online data science courses, but I feel like most of them just give you a piece of the knowledge. I was specifically looking for a program that offered systemic learning. Then I found SIT Learning. Their unique curriculum is why I choose the Data Science Bootcamp."❞

Before: Ph.D. in transportation planning and management

After: Data Scientist at Saporo

Anselme Borgeaud

Data Science

❝“Looking back these were three incredible months in Zurich, and I would definitely recommend it to anyone considering joining the boot camp.”❞

Before: Ph.D. in Seismology

After: Asset Management at Pictet Group

Tiffany Carruthers

Data Science

❝After completing the Bootcamp, I was able to land a job through SIT’s professional network.❞

Before: Data Engineer

After: Data Engineer at Axpo

Lingxuan Zhang

Data Science

❝"I decided to research some online data science courses, but I feel like most of them just give you a piece of the knowledge. I was specifically looking for a program that offered systemic learning. Then I found SIT Learning. Their unique curriculum is why I choose the Data Science Bootcamp."❞

Before: Ph.D. in transportation planning and management

After: Data Scientist at Saporo

Where our students work

Get your dream job - we'll support you along the way!

What you will learn

Preparation work 1-2 weeks

To get the best out of our Data Science course good preparation is key. Therefore, we have put together a preparation course that specifically prepares you for it. Depending on your previous knowledge, this requires about 1-2 weeks of intensive work.

Learn about statistics, basic probability, calculus and linear algebra, version control, and Python.
If needed, our team is on call via Slack to support you.

Open session

Meet your fellow students for an evening session the week before the program starts. Review the preparation work and exchange your problems and solutions with the class.

1

Statistics & experimental design 6 days

Use statistical methods to assist decision-making using critical methodologies like A/B testing.
Apply inferential statistics, parameter estimation, and hypothesis testing on Data Science problems.
Learn about probabilistic modeling and generalized linear models and solve real-world problems.

2

Data Science toolkit 6 days

Learn the tools and programming languages relevant to Data Science.
Python fundamentals for Data Science, version control (git and GitLab), organizing and structuring data science projects.
In-depth data wrangling in Python (accessing online data through APIs, data cleaning, and exploration with Pandas).
Work with both JupyterLab and integrated development environments.

3

Data visualization 4 days

Use advanced visualization techniques for extracting actionable insights from data and create visually compelling stories.
Create interactive figures and even full-fledged dashboards leveraging tools like Matplotlib, Seaborn, Plotly, and Dash.

4

Machine Learning I 4 days

Gain an in-depth view of supervised learning methods (regression and classification).
Learn ML core concepts (ex: gradient descent, linear vs non-linear models, loss functions, cross-validation, tuning).
Solve real-world scenarios, including tackling imbalanced data and selecting suitable models.
Build advanced end-to-end machine learning pipelines.

5

Machine Learning II 5 days

Optimize model performance using hyperparameter tuning.
Use model interpretation frameworks such as LIME and SHAP.
Apply unsupervised learning methods (clustering, outlier detection, and dimensionality reduction).
Learn about the most recent advancements, applications, and frameworks for Auto-ML (PyCaret, TPOT, and Auto-Sklearn).

6

Deep Learning 5 days

Learn the theory and history behind neural networks and deep learning.
Build your own networks using TensorFlow and Keras - Artificial Neural Networks and Convolutional Neural Networks.
Use deep transfer learning and state-of-the-art Deep Learning models to solve computer vision problems like image classification and segmentation.
Interpret and explain deep learning models for vision using techniques like Grad-CAM.

7

Natural Language Processing (NLP) 4 days

Learn NLP core concepts (e.g.: named entity recognition, topic modeling, document classification, similarity, embeddings, etc.).
Learn and practice how to transform unstructured text into structured data and train classical ML models.
Solve diverse problems like classification, recommendations, summarization, named entity recognition, and more.
Use the latest state-of-the-art Deep Learning models, including transformers to solve more complex tasks (language translation, contextual similarity, search, and more).

8

Machine Learning Engineering 6 days

SQL is one of the most requested job interview skills. In 3 days, we bring you from a complete beginner to an advanced level so that you are well prepared for your future job interviews.
Learn how to approach a Data Science project effectively by using conventional workflows and creating a clean project structure.
Learn about MLOps best practices such as model & data version control, experiment tracking, model and code testing, and CI/CD for ML projects.
Use Docker containerize and serve your model, making it accessible via an API that you will deploy on a cloud server.

9

Capstone project weeks 9-12

Solve real Data Science problems provided by companies and research institutions.
Experience the complete Data Science process: from defining your business problem, exploring the data, applying suitable machine learning techniques, to finally delivering a functional prototype.
Get coached and present your work in a public meetup.

Application process

Apply to the program

Send us your CV or LinkedIn profile

First motivational interview with Constructor Learning

Prepare for the technical interview

Pass the technical interview

Pay a deposit to secure your spot

Complete your preparation work before the Bootcamp starts

Get ready for the course

Free Data Science intro course

Online

Self-paced

Free of charge

Learn about Python, the data science project lifecycle, and practice on a real-world data science problem in this free self-paced online tutorial. By completing this course, you will gain a better understanding of the Data Science world and increase your chances of being accepted into the Bootcamp.

Estimated time to complete: 15 hours

Start learning

Weekly schedule

(CET)

Mo

Tue

Wed

Thu

Fr

Sat

09H00

12H00

13H00

18H00

On-site

Schedule doesn't fit your needs? Check out our Part-Time program.

Lecture

Learn from our instructors who are experts in their respective fields and get introduced to new topics during live lectures.

Practice

Work on a set of interesting and challenging exercises related to the topics covered during morning lecture. Practice your team-building skills by doing group projects together with your peers.

Topics

Data Analytics

Examine large and complex data sets to uncover insights, trends, and patterns that can inform decision-making.

Python SQL Numpy Pandas Jupyter Notebook Matplotlib Streamlit

ML & AI

Train computer algorithms to learn patterns and make predictions or decisions without explicit instructions, based on data inputs.

Scikit-learn SciPy TensorFlow PyCaret

DevOps

Efficiently manage team tasks and collaborate using GitLab. Gain the ability to deploy your applications on the web and seamlessly connect them to each other.

GIT GitLab Docker AWS

Python

Python is taking over the world!

Python is the market leader in many sectors:

Data Analytics
Machine Learning
Artificial Intelligence
Scientific Research
Software Prototyping
And more...

Hands-on

Hundreds of hours of hands-on training

Take part in the AI revolution!

Our instructors

One of our biggest assets is our instructors. Besides our internal Data Science team, we always bring in selected external experts from industry. These external instructors keep us in constant contact with trends and requirements in industry and allow us, as well as yourself, to build a well-established network. We really care about selecting instructors with outstanding didactic skills and constantly improving our teaching based on your feedback. Have a look at our impressive team of instructors and their diverse backgrounds.

Instructors

Our capstone projects

What clearly sets us apart from other Bootcamps is that we organize REAL projects with REAL companies. We do not rest when it comes to finding companies who can provide exciting projects for you and your course mates. This gives your portfolio a big push, and you wouldn't be our first student who might get hired by one of these companies after the project. Also, we are not shy! If you are interested in a particular company, we are very happy to contact them to see whether we can start a project together.

Final projects

Finish your professional transformation by working on an industry relevant capstone project.

Preparation phase

Organize your project

Receive and/or set the requirements
Set milestones

Development/Creation phase

Work in a team

Use collaborative tools
Split and coordinate different tasks
Learn from your fellow teammates
Build your first real world project

Presentation

Leave your first mark in the industry

Present your capstone project with your team mates in front of attendees from our network.

Sign up for the next final presentations on 28. Sep 23.

brain-mri-classification-kantonsspital-winterthur

Data Science

Brain MRI Classification in collaboration with Kantonsspital Winterthur

Project by:

Cornelia Schmitz, Norbert Bräker

Earn a Certificate of Accomplishment

Share your Certificate on social networks, printed resumes, CVs or other documents. Boost your career with the new skills that you gained.

Mentorship

At Constructor Learning, we mentor our students, with a focus on placing their individual needs and goals at the center of our approach. Our goal is to empower our students to succeed by providing them with the guidance and support they need to achieve their full potential.

Ongoing mentorship

No need to schedule appointments; receive prompt and continuous feedback. Our teaching assistants are readily available to assist you.

Real-world projects

Effective mentoring equips you with the skills to tackle actual work challenges. Our capstone projects mirror real industry projects, bringing together all that you have learned.

Career coaching

We assist you in finding new job opportunities and showcasing your qualifications to potential employers.

Live lectures

Learning can be tough, and that's why the dropout rate for self-paced courses is as high as 85%. We recognize that interactive, human-led instruction is crucial to achieving ambitious learning objectives.

Choose your location

Zurich

Munich

Bremen

Remote

Join us from everywhere in the world

We offer our courses at different locations. Learn remotely from anywhere in the world or attend on-site at one of our locations. Click on your preferred location to learn more.

Financing options

At Constructor Learning, we believe that finances should never be a barrier to accessing the education and training that can help individuals achieve their goals. That's why we offer a variety of financing options to make our courses more accessible to a diverse range of students. We also work with external organizations that provide financial assistance to those in need.

Learn more

Upcoming events

Attend one of our events. Discover our upcoming workshops, info sessions, final presentations and webinars on trending topics.

Final presentations of our Full-stack and Data Science students
28. Jul 23, 06:00 PM - 08:00 PM GMT+2
Flössergasse 2, 81369 Munich
Get ready to witness the ultimate showdown of brainpower and creativity as our bootcamp graduates present their final projects to a jam-packed audience of students, alumni, family members, friends, and companies! These incredible projects were developed in just three weeks, as the culmination of a three-month training period. But wait, there's more! Constructor Learning cordially invites you to join us for this epic event, where you'll have the chance to marvel at these exciting projects and soak up some serious inspiration. Don't miss out on this incredible opportunity to witness the future of tech firsthand. Register now!
Details
Final presentations of our Full-stack and Data Science students
28. Sep 23, 06:00 PM - 08:00 PM GMT+2
Flössergasse 2, 81369 Munich
Get ready to witness the ultimate showdown of brainpower and creativity as our bootcamp graduates present their final projects to a jam-packed audience of students, alumni, family members, friends, and companies! These incredible projects were developed in just three weeks, as the culmination of a three-month training period. But wait, there's more! Constructor Learning cordially invites you to join us for this epic event, where you'll have the chance to marvel at these exciting projects and soak up some serious inspiration. Don't miss out on this incredible opportunity to witness the future of tech firsthand. Register now!
Details

FAQs

What’s the non-technical interview?

Lasting 20 minutes in-person or over video call, it gives us a chance to get to know you, your professional experience, motivation and goals for participating in the program.

How many students are there per class?

To maintain a high level of interaction and instruction, each class has an average of 10 to max. 20 students (in-class).

Is the duration of the Bootcamps long enough?

Absolutely. For the Full-Stack and Data Science programs, 12 weeks of intensive practice (40 hours in the classroom with an additional 20-30 for course work per week) will give you what it takes to step into one of these fields.

What coding level do I need?

Though coding experience is not necessarily a prerequisite, we expect you to have been exposed to programming before, whether in industry, academia, or self-study. Motivation, hard-work, and drive are what we're most looking for.

I’d rather participate from another location. Can I attend the program remotely?

Absolutely. For those interested in this option, please select it on the application form.

Is there a difference between the in-person and remote option?

None at all. You’ll be joining the in-class participants for the same program and follow via our live stream platform. You’ll get the same attention from our staff as if you were on site.

What’s the technical interview like for the Data Science program?

The candidate will receive an email with a list of Python tutorials to complete before the interview. The interview date and time will be set such that there is around one week to get prepared for it.
On the day of the interview, the candidate will receive a data challenge by email and will have 2 hours to work on it. After submitting the results, a SIT Learning team member will connect to discuss the results of the Data Challenge (around 15 min). Subsequently, a 30 minute Python coding assessment is conducted to determine the candidate’s structural and logical thinking. The whole process will take 2 hours, 45 min and be based on the tutorials sent before.

Contact us

Instructors

Dr. Ekaterina Butyugina

Data Science Program Manager & Instructor

Bio

Ekaterina studied mathematics at university and worked as Junior Researcher in Russia where she did her PhD in Continuum Mechanics. Looking for the opportunity to find something close to science but more dynamic and applicable to real life, she joined the Data Science program, then stayed on as a TA and later joined the team as a Data Science Consultant. She likes to work with data and apply both analytical and creative approaches, trying new techniques and sharing them with other people.

Sekhar Ramakrishnan

Instructor

Bio

I love making data speak. Visualizations combine programming and art, logic and aesthetics, to help data communicate; it is always satisfying to guide students through these disparate disciplines to learn to read, appreciate, and design their own visualizations.

Gerry Liaropoulos

Instructor

Bio

As an experienced Data Scientist in the fascinating sector of Life Sciences, I am using a variety of Machine-Learning methods to help the industry make more informed decisions with the end goal of effecting a positive change on patients’ lives.

Dr. Mark Rowan

Instructor

Bio

What drives you? For me, it's about using data to tell a story and change the world. Whether it's neuroscience, aerospace, telecoms, insurance, or voice tech - I love getting into the data and making things happen.

Dipanjan Sarkar

Lead Data Scientist & Instructor

Bio

Dipanjan (DJ) is a Lead Data Science Consultant & Instructor, leading advanced analytics efforts around Computer Vision, Natural Language Processing and Deep Learning. He is also a Google Developer Expert in Machine Learning. Dipanjan has advised and worked with several startups as well as Fortune 500 companies and is also a published author, having authored several books on R, Python, Machine Learning, Natural Language Processing, and Deep Learning. He loves sharing his knowledge with the community to help them grow in their own journey in Data Science.

Badru Stanicki

Instructor

Bio

With a Masters in Physics, Badru got into scientific programming and Data Science during his time at the German Aerospace Center in Spain. After working several years in research, he moved into Data Science, first as a student and then as a team member. His main interests are DataOps and Time Series Analysis.

Magdalena Surówka

Instructor

Bio

Statistics enables you to understand the world around you. To discover new relationships, and to model their impact. As an independent Data Scientist, I help companies find such insights. As a statistics instructor, I show students how to frame the problem, and draw conclusions.

Dr. Marie Bocher

Data Science Consultant

Bio

Marie has 7 years of experience in developing, deploying, and teaching machine learning and statistical models. At SIT, she consults companies and mentors individuals on various data science and software engineering topics. She is dedicated to sharing her expertise on these topics with a hands-on, interactive approach to teaching.

Afke Schouten

Director of Studies - AI management, HWZ

Bio

Afke Schouten studied mathematics at the University of Leiden and econometrics and management science at the Erasmus School of Economics. As a management consultant and senior data scientist, she has led various AI projects and set up AI organizations for international and Swiss companies. She is currently working as a researcher and freelancer in the area of AI management and is the director of studies for AI Management at the HWZ University of Applied Sciences. It is her mission is to help organizations generate true business value with AI and support organizations in creating an environment in which Data Scientists can thrive.