Data Science Bootcamp

Become a Data Scientist in 12 weeks by acquiring the required knowledge in Python, Machine Learning, Deep Learning, and NLP. Solve an industrial data problem for the Capstone project.

Apply now
Data Scientist
clock

Full-Time

1
2

weeks

remote

On-site / Remote

language

English

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.

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Upcoming dates

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Students say

Lina Siegrist-Choo

Lina Siegrist-Choo

Data Science

I can definitely say that I might not be able to achieve my career plan without joining Constructor Learning.

BeforePostdoctoral Researcher

AfterJunior Data Engineer at Nestlé

Tiffany Carruthers

Tiffany Carruthers

Data Science

After completing the Bootcamp, I was able to land a job through Constructor's professional network.

BeforeData Engineer

AfterData Engineer at Axpo

Seth Dow

Seth Dow

Data Science

I believe that the personnel at Constructor are top notch, and they are invested in your success.

BeforeMath Teacher

AfterData Analysis at Migros

Where our students work

You can work here too! Get your dream job, we will help you along the way

Google
Swisscom
Ava
Ebay
Swiss International Air Lines

What you will learn

0

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.

0

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.

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

Weekly schedule

(CET)

Mo

Tue

Wed

Thu

Fr

Sat

09H00

12H00

13H00

18H00

On-site
On-site
On-site
On-site
On-site
On-site
On-site
On-site
On-site
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.

Tools we teach

Python
For many reasons, the fastest-growing programming languages globally: its ease of learning, the recent explosion of the Data Science field, and the rise of Machine Learning. Python also supports Object-Oriented and Functional Programming styles, which facilitate building automated tasks and deployable systems. There are plenty of Python scientific packages for Data Visualization, Machine Learning, Natural Language Processing, and more.
TensorFlow
TensorFlow is an open-source software library for Deep Learning developed by Google. Across a range of tasks, it can build and train neural networks to detect and decipher patterns and correlations analogous to the learning and reasoning that humans use. It is highly optimized to run in computational servers where task parallelization is possible.
SQL
Relational Database Management Systems (RDMS) are present in any kind of data-oriented system. RDMS are comprised of columns and rows to store data within a structured format and are a potent tool to store massive amounts of information. SQL is the language to query and manipulate data in RDMS and is, for this reason, very relevant in the field of Data Science.
Scikit-learn
Scikit-learn is the most established and developed Machine Learning library. It features various classification, regression and clustering algorithms, including support vector machines, random forests, gradient boosting, k-means, and DBSCAN. It directly interoperates with the numerical and scientific libraries NumPy, Pandas, and SciPy.
Git
Git is a free and open-source version control system designed to handle everything from small to huge software projects (Linux kernel). It allows you to keep track of the code changes and collaborate with others on a project. You will use it daily during our Data Science course.
NumPy & Pandas
NumPy is the fundamental package for scientific computing with Python, adding support for large, multi-dimensional arrays, along with an extensive library of high-level mathematical functions. Pandas is a library build on top of NumPy for data manipulation and analysis. The library provides data structures and a rich set of operations for manipulating numerical tables and time series.
Cloud Services
More and more companies are moving to cloud computing systems. It has become the primary location for businesses to store data, train ML models, and deploy production systems. Having experience with a cloud system will make you stand out in today's job market.
PyCaret
PyCaret is an open source, low-code machine learning library in Python that allows you to go from preparing your data to deploying your model within minutes. It also has Automated ML capabilities to build a suite of trained models in minutes on any problem and assist with model selection and tuning.

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

How your final project could look like

brain-mri-classification-kantonsspital-winterthur

Brain MRI Classification in collaboration with Kantonsspital Winterthur

Data Science

Project by: Cornelia Schmitz, Norbert Bräker

More info
globus

Using AI for automatic feature prediction from product images

Data Science

Project by: Valeria Polozun, Seth Dow

More info
swiss

Classification of NOTAMs for SWISS International Airlines using AI

Data Science

Project by: Jean Coupon

More info

Application process

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

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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.

Certificate

We've got your back!

We like giving you individual attention, which is why you will have several one-on-one sessions throughout the Program to speak with our program manager or one of our instructors.

We support you to find your next dream job

  • Individual progression sessions
  • One-to-one sessions with career advisors
  • Cover Letter and CV writing sessions
  • Sending your CV to our network of hiring companies
  • In house events such as our Hiring Day
  • Opportunity to collaborate with companies on a project
Coaching

Choose your location

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.

Upcoming events

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

  • Final presentations

    17. Feb 23, 06:00 PM - 08:00 PM GMT+1

    Heinrichstrasse 200, 8005 Zurich or online via Zoom

    Join us on Friday, February 17th, 2023, at 6 PM to see what our graduates have been up to in the final weeks of their bootcamp. Our talented students have been working hard to develop innovative solutions to real-world problems using Data Science and Full-stack development skills. You'll have the opportunity to hear from them as they present their projects and share their insights and experiences. Take advantage of this exciting event! Register now to reserve your spot. We hope to see you there!

    Details

  • Introduction to HTML & CSS workshop

    21. Feb 23, 05:00 PM - 06:30 PM GMT+1

    Online via Zoom

    Join us for our upcoming online HTML and CSS workshop on Tuesday, February 21st from 5-6:30 PM. Our experienced instructor will guide you through the fundamentals of HTML and CSS, including positioning, Flex, animations, etc. then take what you have learned and dive into a couple of exercises. Whether you are a beginner or have some experience with HTML and CSS, this workshop will provide valuable tips and techniques to improve your web development skills. Don't miss out on this opportunity to learn from the best and take your web development career to the next level. Space is limited, so register now to secure your spot. We hope to see you there!

    Details

  • Data analytics workshop

    23. Feb 23, 05:00 PM - 07:00 PM GMT+1

    Online via Zoom

    Join Dipanjan on Thursday, February 23, 2023, from 5 - 7 PM and get an introduction to data analytics. Dipanjan is our lead data science consultant & instructor, leading advanced analytics efforts around Computer Vision, Natural Language Processing and Deep Learning. He will lead you through python and data processing basics, talk about framing data science problems, and briefly discuss how to analyze and visualize unique patterns. At the end of the workshop, you will create a model that can predict housing prices using machine learning. If you are interested in data science and data science-related topics, this event is for you. Register today to save your seat.

    Details

  • Final presentations - part-time students

    24. Feb 23, 06:00 PM - 08:00 PM GMT+1

    Heinrichstrasse 200, 8005 Zurich or online via Zoom

    Join us on Friday, February 24th, 2023, at 6 PM to see what our part-time students have been up to in the final weeks of their Bootcamp. Our talented students have been working hard to develop innovative solutions to real-world problems using Data Science and Full-stack development skills. You'll have the opportunity to hear from them as they present their projects and share their insights and experiences. Take advantage of this exciting event! Register now to reserve your spot. We hope to see you there!

    Details

  • Online information session

    28. Feb 23, 06:00 PM - 07:00 PM GMT+1

    Online via Zoom

    Join us on Wednesday, February 28, 2023, from 6 PM until 7 PM for an exciting information session about Constructor Learning and our programs. Whether you're a beginner looking to learn a new skill or an experienced professional looking to advance your career, this information session is the perfect opportunity to learn more about our bootcamps and how they can help you reach your goals. This online information session will provide an overview of our programs, including the curriculum, career outcomes, and admissions process. You'll have the opportunity to ask questions and get insights from our instructors. Don't miss this opportunity to take the first step towards a rewarding new career in Data Science, Full-stack development, or UXUI design. Sign up now to reserve your spot in the information session. See you soon!

    Details

  • Learn how to code with Python

    15. Mar 23, 06:00 PM - 07:30 PM GMT+1

    Online via Zoom

    Join us for our upcoming online Introduction to Python programming workshop on Wednesday, March 15th, 2023, from 6 - 7:30 PM. Whether you're new to programming or looking to expand your skills, this workshop is the perfect opportunity to learn the basics of Python programming and take your skills to the next level. Led by expert Python programmer Ansam Zedan, you will be guided through the fundamentals of programming in Python, including variables, conditions, and loops. But that's not all - you'll also have the chance to personalize your own turtle and give it commands to create unique drawings on the screen. By the end of the workshop, you will have a solid understanding of Python programming and the ability to create your own digital masterpieces. Don't miss out on this exciting opportunity - register now to secure your spot! We can't wait to see you there.

    Details

Empty room with chairs

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 Constructor 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

Team Member

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.
Team Member

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.
Team Member

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.
Team Member

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.
Team Member

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.
Team Member

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.
Team Member

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.
Team Member

Dr. Marie Bocher

Data Science Consultant

Bio
Marie has 7 years of experience in developing, deploying, and teaching machine learning and statistical models. At Constructor Learning, 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.
Team Member

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.

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