Part-Time CourseData Science Bootcamp

Boost your career with our 22-week part-time Bootcamp and learn new skills in Python, Data Analytics, Machine Learning, Deep Learning, NLP and Generative AI.

Apply now
Data Science student learning
clock

Part-Time

2
2

weeks

zurich

Zurich

language

English

Program overview

Do you want to build on your existing skills to advance your career, learn new technologies, or get back into the workforce after a long break? 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. In addition, our part-time program allows you to continue working 100%.
Data Science Intro Video

Upcoming Dates

Course dates

Sep 10 - Feb 21

Apply by

Aug 09

Tuition

12'700 CHF

Schedule

  • Tue

    Remote

    • 18.00 - 21.00Lecture
  • Thu

    Remote

    • 18.00 - 21.00Practice
  • Sat *

    On-site

    • 09.00 - 12.00Lecture
    • 13.00 - 16.00Practice

    * The course takes place every second Saturday.

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

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

Where our students get jobs

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

Axpo
Swiss International Air Lines
Google
Swisscom
Axa
Ergo Group
Ebay
Novartis
Adobe
Pagoda
Elca
Ginetta
Atos
Ippen Media
Roche
ETH Zurich
Pictet
Upc
Qualityminds
Avrios
Ergon
Axpo
Swiss International Air Lines
Google
Swisscom
Axa
Ergo Group
Ebay
Novartis
Adobe
Pagoda
Elca
Ginetta
Atos
Ippen Media
Roche
ETH Zurich
Pictet
Upc
Qualityminds
Avrios
Ergon
APGSGA
Sygnum
Web Republic
Synvert
Brack
UBS
Globus
Credit Suisse
Migros
Ruag
Accenture
Ernst & Young
Dormakaba
Comparis
Climeworks
Mediaire
Six Group
Swiss Re Group
SAP Software Solutions
Edge5
Smartfactory
APGSGA
Sygnum
Web Republic
Synvert
Brack
UBS
Globus
Credit Suisse
Migros
Ruag
Accenture
Ernst & Young
Dormakaba
Comparis
Climeworks
Mediaire
Six Group
Swiss Re Group
SAP Software Solutions
Edge5
Smartfactory
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Thi Tuyen Nguyen

Thi Tuyen Nguyen

Data Science

The intense curriculum of the bootcamp pushed me outside my comfort zone, enhancing my resilience and passion for continuous learning while equipping me with essential skills for a transformative career in data science.

BeforePostdoctoral Researcher

AfterArtificial Intelligence Intern at Baader Bank AG

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What you will learn

  • After applying

    Preparation work

    Our Data Science course is very demanding and intensive. Therefore, we have put together a preliminary 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 Discord to support you.
  • Week before start

    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.
  • Week 1 - 3

    Data Science toolkit

    • Learn the tools and programming languages relevant to Data Science.
    • Python fundamentals for Data Science, version control (git and GitLab), SQL databases, 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.
  • Week 4 - 5

    Statistics & experimental design

    • 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.
  • Week 6 - 7

    Data visualization

    • 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.
  • Week 8 - 11

    Classical & advanced Machine Learning (ML)

    • Build advanced end-to-end machine learning pipelines.
    • Gain an in-depth view of supervised learning methods (regression and classification), as well as unsupervised learning methods (clustering, outlier detection, and dimensionality reduction).
    • 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, selecting suitable models, optimizing model performance using hyperparameter tuning, and model interpretation using frameworks such as LIME and SHAP.
    • Learn about the most recent advancements, applications and frameworks for Auto-ML (PyCaret, TPOT and Auto-Sklearn).
  • Week 12 - 14

    Deep Learning

    • 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.
  • Week 15 - 17

    Natural Language Processing (NLP)

    • 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 features and train classical ML models.
    • Solve diverse problems like classification, recommendation, summarization, named entity recognition, and more.
    • Use Deep Learning models and Transfer Learning including Transformers to solve more complex tasks (language translation, contextual similarity, semantic search, and more).
    • Learn about Generative AI for NLP, Prompt Engineering and Large Language Models (LLMs) like ChatGPT to solve diverse NLP tasks including QA Chatbots.
  • Week 18

    Machine Learning Engineering

    • 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.
  • Week 19 - 22

    Capstone project

    • Solve real Data Science problems from our carefully curated list of pre-defined projects or even better, bring your own data and Data Science problem!
    • 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

  • checkApply to the program here
  • check

    Send us your CV or LinkedIn profile

  • check

    First motivational interview with Constructor Academy

  • check

    Prepare for the technical interview

  • check

    Pass the technical interview

  • check

    Pay a deposit to secure your spot

  • check

    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

Topics

Data Analytics

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

ML & AI

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

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.

Python

Python is taking over the world!

Python is the market leader in many sectors:

  1. Data Analytics
  2. Machine Learning
  3. Artificial Intelligence
  4. Scientific Research
  5. Software Prototyping
  6. Generative AI
  7. And more...

Hands-on

Over 360 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.


There is no upcoming final projects date fixed yet. Sign up to our newsletter if you want to get notified whenever the next date gets published.

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brain-mri-classification-kantonsspital-winterthur
Data Science

Brain MRI Classification in collaboration with Kantonsspital Winterthur

Project by:
Cornelia Schmitz, Norbert Bräker

Project description
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See full list.

Choose your location

Visit our campus in Zurich

Would you like to see what your time at Constructor Academy could be like and where our students spend most of their time? Then contact us for a visit of our campus.

Constructor Academy
Heinrichstrasse 200
8005 Zürich
+41 (0)44 797 51 43

Schedule a visit

Financing options

At Constructor Academy, 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.

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Certificate from top coding school

Get certified by Constructor Academy, one of the world's top coding academies. Share your certificate on social networks, CVs and more. Boost your career with the new skills that you gained.

Certificate

Upcoming events

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

  • Continuing Education Event | 20 & 21.06.24 | Munich

    calendar20. Jun 24, 11:00 AM - 03:00 PM GMT+2

    map-pinLilienthalallee 40, 80939 München, Germany

    Are you looking to further your education or prepare your team for future challenges? The Continuing Education Fair offers a comprehensive overview of qualification and training opportunities in Munich and the surrounding areas. Visit our stand! Learn about our career programs and short courses. Meet many training providers, attend exciting presentations, and get personalized advice on funding and further training options.

  • Continuing Education Event | 20 & 21.06.24 | Munich

    calendar20. Jun 24, 11:00 AM - 03:00 PM GMT+2

    map-pinLilienthalallee 40, 80939 München, Germany

    Are you looking to further your education or prepare your team for future challenges? The Continuing Education Fair offers a comprehensive overview of qualification and training opportunities in Munich and the surrounding areas. Visit our stand! Learn about our career programs and short courses. Meet many training providers, attend exciting presentations, and get personalized advice on funding and further training options.

  • Open day | Zürich

    calendar22. Jun 24, 02:00 PM - 04:00 PM GMT+2

    map-pinLintheschergasse 7, 8001 Zürich

    Come to our open house on Saturday, June 22! We are excited to announce that we are moving locations to serve you better. Join us to explore our newest campus, conveniently situated in the heart of Zürich. You'll also have the opportunity to learn about our career programs in tech and our short courses in Python and Generative AI. See you there!

Empty room with chairs

FAQs

  • What’s the non-technical interview?

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    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.

  • When do I have to pay the tuition fee for the part-time Bootcamps?

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    Upon enrollment, you are required to pay a non-refundable CHF/EURO 3,500 deposit to reserve your seat in the program. 1/2 of the remaining balance is due by the end of the second week of the program and 1/2 by the third month of program.

  • What's the course schedule for the part-time Bootcamp?

    caret

    The part-time Bootcamp is a 22-week program, with lectures every Tuesday and Thursday from 6pm - 9pm and every other Saturday. In addition, our students invest a few extra hours of their free time to review what they have learned and work on projects.

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

    caret

    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 Academy 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.

  • Which job positions can I apply for after the bootcamp?

    caret

    Completing our Data Science Bootcamp opens up numerous possibilities in the tech job market. Here are some of the job positions that you can apply for as a graduate: • Data Scientist • Data Analyst • Data Engineer • Data Architect • Machine Learning Engineer • Business Intelligence Engineer

Contact us

Instructors

Team Member

Marcus Lindberg

linkedin

Data Science Program Manager

Starting his career in clinical immunotherapy research, Marcus was exposed to the pressing need for better ways to make sense of patient data. With a growing interest in personalized therapies, he pursued a MSc in Bioinformatics at the University of Edinburgh and joined ETH Zürich’s Clinical Bioinformatics Unit. Now at SIT Learning, he is able to keep refining his analytical toolbox while helping people reach their goals along the way.

Team Member

Dr. Mark Rowan

linkedin

Instructor

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
company

Gerry Liaropoulos

linkedin

Instructor

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

Patrick Senti

linkedin

Freelance Analytics Consultant

Patrick has been building analytics solutions since 1995, applying machine learning, data engineering, data analytics & visualization. Helping customers in the finance, transportation and retail industries his experience includes software engineering & architecture in distributed systems from enterprise backends to mobile & IoT systems. Senior BI/Data Science & Software Engineer since 1995 * Applied data science, data engineering, software engineering, big data * Wide industry experience in Finance, retail, logistics Roles * Data scientist/data & ML engineer, software engineering, consulting * Lead Data Analytics Practice at swissQuant * Senior Software Engineering, Tech Lead at Credit Suisse, Logicalis, SAS, IBM Education * CAS ETH Zürich in Computer Science & Distributed Systems * Swiss Dipl. Business Informatics (Professional Master) * Executive MBA Freelance Analytics Consultant, patrick@productaize.io Founder omegaml.io Helping companies to productize and operationalize ML

Team Member

Dr. Ekaterina Butyugina

linkedin

Data Science Program Manager & Instructor

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.

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