Next Program Dates

March 10 - Oct 29

Apply By

24 February

   

Where "BigBluers" got hired

About the Bootcamp

Become a certified Data Scientist

Our Data Science bootcamp is an intensive hands-on training on Data Science, with which you gain all the technical and soft skills and the network you need to launch your career in Data Science.

Experienced data professionals bring real-world insights to the classroom, and career advisors help you get hired as Data Scientist, Data Analyst, Machine Learning/AI Engineer, etc. 

Master the art of extracting meaningful insights from data, applying Machine Learning to solve business challenges and communicating your results with appealing dashboards.

Who this Bootcamp is for

  • Undergraduates, graduates (Bachelor, Master or PhD) and professionals looking to upskill and work in the fast-growing world of Industry 4.0

  • Career changers eager to reskill and pivot in Data Science

  • People committed to a successful career path who challenge themselves with hard work

Big Blue Benefits

Made by Professionals for Professionals

  • Designed and taught by Data Science industry experts

  • Project-based curriculum with real data and real-world use cases

  • Industrial project to learn how a data scientist plans, communicates and works in a team

  • Familiarity with important technical and soft skills

  • Structured GitHub profile and strong portfolio

  • Career coaching and Job assistance

  • Hiring Network

Our Method

Active Learning

25% theory - 75% practice

During each day we spend max 25% of the time for theory (lecture, live coding, code reviews) in order to get you as fast as possible to the exercises, where the real learning and fun begins!

Experienced Professionals

Real-world knowledge

Our instructors are professionals in the industry. With their real-world experience, they will help you learn practical and soft skills and build a strong foundation to begin your data science career.

Alumni

Our Graduates Get Hired in Less Than 3 Months!

Program Outline

Curriculum in Modules

Each module introduces new concepts, leading to the final project where you apply everything you've learned. This hands-on experience solidifies your new in-demand skills and demonstrates your ability to put them to use.

Get the curriculum

Preparation

Fundamentals of Python

Start with the Pre-work at home to brush up your knowledge in Python, Maths and Statistics. These 40 hours of preparation will get you ready for the first day. It must be completed before the first day of class.

Tools that will be used:

 

Module 1

  • Exploratory Data Analysis

Learn Advanced Python for Data Science and Business Analytics, make EDA using Python, Pandas and share your code using Git.

  • Data Visualization

Create interactive dashboards with Plotly & Dash, Streamlit and Power BI, and communicate your results with business-like presentations.

  • Github Project: Exploratory Data Analysis & Insights

 

Tools that will be used:

          

Module 2

  • Data Access from Any Source

Learn SQL, make advanced queries and access data from databases. 
Use APIs or web scraping to get data for your projects.

  • Interactive Dashboards for Effective Data Storytelling

Work on Power BI, Plotly & Dash and MongoDB.

  • Github Project: Interactive dashboard

 

Tools that will be used:

      

Module 3

Learn all the Machine Learning algorithms used by the industry and use various optimization techniques to build your models. Get familiar with Artificial Intelligence.

  • Supervised Machine Learning

Regression and Classification: Use algorithms like Random Forest, XGBoost for machine learning models optimization in action.

  • Github Project: Classification or regression
     
  • Unsupervised Machine Learning

K-means clustering, Hierarchical clustering, Anomaly detection, Principal Component Analysis, Apriori algorithm, Singular value decomposition, t-sne, outlier detection.

Clustering and Labeling: Use K-Means, Hierarchical clustering, DS-SCAN to find common patterns, and Isolation Forest, Local Outlier Factor for outlier and anomaly detection.

  • Github Project: Clustering

 

Tools that will be used:

      

Module 4

  • Big Data

Access and manipulate large amounts of text data from NoSQL servers (MongoDB).

  • Deep Neural Networks

Neural Networks and Convolutional Neural Networks (Keras) for image classification, using deep learning neural networks.

  • Natural Language Processing

Classic NLP for sentiment analysis, topic modeling, and recommender systems.
Learn to build Large Language Models (LLMs) to master Generative AI (Chatbots).

  • Time Series Analytics

Use forecasting algorithms (ARIMA and Prophet) for pattern detection, inferential statistics and forecasting.

 

Tools that will be used:

      

Module 5

Final Project

Work on your final project solving a real Data Science challenge, in a direct collaboration with a company.
Get the opportunity to network with companies actively seeking Data Scientists during Career Day.

Industrial Project

Work on a Data Science project with a company

At the final phase of the Bootcamp you practice everything you learned by working on a real Data Science project for a company.

Real Data Science project

You get to work on a real-world business project alongside a partnering company in our campus for four weeks.

Professionally done

You will demonstrate your ability to deliver an end-to-end structured project and meet deadlines.

Full support

Our instructors offer ongoing guidance, mentorship and support throughout your project work.

Career day

The Bootcamp concludes with a Career Day, where you present your project and meet prospective employers.

Duration

25 weeks
500 hours

Schedule
Mon-Wed-Thurs
18:00-22:00
Saturday
10:00-17:00
Language
In class: Greek
Materials: English
Prerequisites
Μath, stats, and Python basics
Our Impact

50

Companies Trusting Us

130

Industry Projects

280

Successful Graduates

12000

Teaching Hours

Career Support

We’ve got your back

Career Options

After completing your training, you’ll be confident to apply for various data roles, depending on your prior experience and field.

Career Coaching

Workshops on creating a standout CV and LinkedIn profile, mock technical interviews, and support throughout the hiring process.

Hiring Network

We link you with industry professionals and companies, expanding your network and supporting your career goals.

Tuition Fees & Dates

Kickstart Your Career in Data Science!

Special Offer

10 Mar

Start Date

24 Feb

Last Apply

12

Seats left

4.300€ 3.900€

Tuition

Tuition fees are payable in up to 3 or 4 installments. For more details about payment have a look at our FAQ.
Special discounts for companies (2+ participants), contact us.

Application Process

Start your Application

Apply to the Program

Fill in and submit your application. Tell us about yourself and your motivation to enroll.

Personal Interview

We reach out to schedule an interview with a member of our team. We'll discuss your technical background and career goals, and provide details about the course.

Technical Interview

We will invite you to a second interview with one of our Data Scientists to assess your programming skills and critical thinking through a discussion.

You can prepare yourself by watching the Introduction to Python for Data Science course on YouTube.

Welcome to Big Blue!

You're ready to embark on your Data Science journey. You'll receive the Prep-Work exercises to work on before your first day of the Bootcamp.

Job-ready Portfolio

Industrial project to showcase your skills

Work on a real-world data-science business project with a partnering company, present it to an audience and meet prospective employers. 

FAQ

Data Science is the interdisciplinary field that combines statistical methods, machine learning, artificial intelligence, and technology to extract insights, knowledge and solutions from structured and unstructured data.

It's important because it enables organizations to make informed decisions, discover patterns, and gain insights by analyzing vast amounts of data, leading to improved efficiency, innovation, and competitive advantage across various industries. It also drives advancements in fields like healthcare, finance, and technology, by enabling predictive analytics, automation, and the development of intelligent systems.

A data scientist can work in various fields, including healthcare, finance, retail, marketing, sports, and HR, applying their skills to roles such as Data Analyst, Machine Learning Engineer, Business Intelligence Analyst, Quantitative Analyst, Data Engineer, or AI Specialist. These professionals use data to drive decisions, optimize processes, and create innovative solutions across diverse industries.

A data scientist focuses on building predictive models and developing algorithms using advanced machine learning techniques, while a data analyst primarily focuses on interpreting and analyzing data to provide actionable insights through statistical methods and visualization.

Our Data Science Bootcamp provides you with 500 hours of all the vital knowledge and skills (Python, Analytics, Machine Learning, Deep Learning, Artificial Intelligence, NLP) to support your career in the Data Science field, while our Data Analytics Bootcamp provides you with 280 hours of in-depth hands-on training to kickstart your career in Data Analytics.

Kickstart your career as a Data Scientist