Full-Time CourseData 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.
Full-Time
weeks
Zurich
English
Program overview
Upcoming Dates
Schedule doesn't fit your needs? Check out our Part-Time program.
Looking for financing? Check out our financing options.
Schedule
- Mon - Fri
On-site
- 09.00 - 12.00Lecture
- 13.00 - 18.00Practice
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 morning 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!
Thi Tuyen Nguyen
❝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.❞
Before: Postdoctoral Researcher
After: Artificial Intelligence Intern at Baader Bank AG
What you will learn
After applying
Preparation work
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 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
Data Science toolkit
- 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.
Week 2
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 3
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 4
Machine Learning I
- 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.
Week 5
Machine Learning II
- 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).
Week 6
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 7
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 8
Machine Learning Engineering
- 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.
Week 9 - 12
Capstone project
- 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.
Mentorship
At Constructor Academy, 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.
Application process
- Apply to the program
Send us your CV or LinkedIn profile
First motivational interview with Constructor Academy
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
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.
LangChainPython
Python is taking over the world!
Python is the market leader in many sectors:
- Data Analytics
- Machine Learning
- Artificial Intelligence
- Scientific Research
- Software Prototyping
- Generative AI
- And more...
Hands-on
Over 480 hours of hands-on training
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.
InstructorsOur 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.
We support you in finding your next dream job:
- 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
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
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.
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.
Upcoming events
Attend one of our events. Discover our upcoming workshops, info sessions, final presentations and webinars on trending topics.
New year, new skills - code your way into 2024
11. Jan 24, 05:00 PM - 06:00 PM GMT+1
Online via Zoom
Dive into the world of full-stack and data science at our online info session! Join us on January 11 at 5 p.m. for an immersive experience. Alumni keynote speakers will share their transformative bootcamp journeys, showcasing capstone projects and insights. Discover how they turned knowledge into thriving tech careers. Engage with program managers during the Q&A to get in-depth details about our courses. Don't miss this chance to explore the endless possibilities our bootcamps offer.
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 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.
Instructors
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.
Instructor
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.
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.
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.
Lead Data Scientist & Instructor
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.
Senior Manager of Data Science
Jesús Humberto Luque Jiménez is a Senior Manager of Data Science at LAYA Group, a Constructor Learning Data Science instructor based in Munich, Germany. With a strong background in data analysis, machine learning, and statistical modeling, he is a true data science expert. Jesús is dedicated to driving innovation and success, overseeing the development of data-driven solutions in the company.
Instructor
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.
Data Science Consultant
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.
Director of Studies - AI management, HWZ
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.
Data Scientist
Pavlin has extensive experience in both teaching and the data science industry. He has served as a lecturer at the ZHAW (Zurich University of Applied Sciences) and Lucerne University of Applied Sciences and Arts, imparting his knowledge to students. Currently, Pavlin is a Full-Stack Data Scientist at UBS, where he plays a pivotal role in the development of a cutting-edge AI Fairness platform and provides AI solutions for lending and sales.
Teaching Assistant - Data Science
Angela holds a Master's Degree in Sustainable Development and worked with data in the non-profit sector for a couple of years. In 2020, she decided to complete the Data Science Bootcamp at Constructor Learning to enhance her skills for creating value from data. She now works as a Data Science Assistant, helping the students grow their own Data Science skills.
Head of Data at Frontify
Having over a decade of experience in the data science industry, Sibel is highly skilled in her domain. She has worked at prominent companies such as Paypal, Ebay, and a Swiss Startup Ava Women, which has helped her accumulate extensive expertise in data-related tasks. Currently serving as the Head of Data at Frountify, she is responsible for developing data ecosystems, monitoring and assessing important KPIs, and setting both strategic and tactical goals for the data team.
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