Turn ODSC into a kickstart virtual bootcamp. Complete your certification path at Ai+ Training.

Avail free access to live and on-demand pre-bootcamp training.

Join Pre-Bootcamp Training

Start learning in the summer with the very fundamentals of data science, followed by a live training to build confidence, and win prizes.

Learn Applied Skills at the Kickstart Bootcamp

Join the 3-day live kickstart bootcamp and learn the languages, algorithms, and tools from some of the leading data scientists in the world

Career Support

Network with attendees from 1,600+ companies and meet over 40 companies hiring directly at ODSC, career days, webinars, resume reviews and more

Get Certified 

Join Ai+ Training and complete your Machine Learning certification

Registration

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 Kick-start your career in data science, from beginner to advanced in just 3 days. Get the skills you need, taught by world-renowned experts

ODSC Kickstart Virtual Bootcamp is the best way to gain in-demand data science skills in the shortest time with minimum investment. Starting in the summer, the Live and on-demand pre-Bootcamp Training will provide the right preparation and confidence to put your practice to work in your learning path.

It’s a truly immersive experience. Over almost a week, you will access an expanse of industry-focused data science topics on a scale not offered elsewhere. Uniquely, you will also get invaluable insights by networking and connecting with hundreds of data science attendees, world renowned-instructors, industry experts, and dozens of top companies seeking the next wave of talent.

Available Specialization Tracks

Attend one of our six specialization tracks or customize it to your own goals

  • Machine Learning with Python

    • Tutorial on Automated Machine Learning
    • Automated Machine Learning with Python – from scikit-learn to auto-sklearn
    • Machine Learning and Statistics: Don’t Mind the Gap
    • Evolution of Efficient and Robust AutoML Systems
    • Introduction to Data Science
    • Hands-on Machine Learning Engineer with scikit-learn

    More sessions coming soon

  • Machine Learning with R

    • Introduction to Data Science
    • Intro Data Analysis using Pandas
    • Automatic and Explainable Machine Learning
    • How to Build and Test a Trading Strategy Using ML
    • Introduction to Data Science

    More sessions coming soon

  • Deep Learning

    • Teaching Machines to Talk: Modern Speech Synthesis with Deep Learning
    • PyTorch 101: Building a Model Step-by-Step
    • Adversarial Attacks and Defence in Computer Vision 101
    • Introduction to Data Science
    • Exploring the Кimworld of Sound Space Using Generative Adversarial Networks
    • Meta-Learning: Learning to Learn

    More sessions coming soon

  • Data Engineering / MLOps

    • Hands-on Machine Learning Engineer with scikit-learn
    • Model Governance: A Checklist for Getting AI Safely to Production
    • Production Machine Learning Monitoring: Principles, Patterns and Techniques
    • Introduction to Data Science

    More sessions coming soon

  • NLP

    • NLP Fundamentals
    • NLP for Transformers
    • Advanced NLP: From Essentials to Deep Transfer Learning
    • Teaching Machines to Talk: Modern Speech Synthesis with Deep Learning

    More sessions coming soon

Our kickstart Bootcamp is fully customizable, you can attend the sessions you want live and on-demand after our conference. Check all available training here – Training Page.

Kickstart Virtual Bootcamp Program Overview

Begin, this spring, with a pre-bootcamp on-demand and live training to build confidence on the core fundamentals of data science, and steadily progress through the bootcamp week with our hands-on training and expert-led sessions and projects. Refer to the timeline below.

Pre-Bootcamp On-demand Training (starts now)

Get started in your learning track with free access to introductory concepts with short, to-the-point and industry driven on-demand courses.

Schedule: Self-paced

Pre-Bootcamp Live Training (FREE & PAID)

Build a foundation of essential hands-on concepts as part of your Bootcamp pass and get complimentary access to one Live training of your choice on the Ai+ Training.

Upcoming live training include:

Free Literacy Pre-Bootcamp Sessions

These 60-minute sessions will help you understand core concepts in Data, Ai, and Programming, to get you to reach for our Bootcamp Program.  Register for FREE or as part of your Bootcamp Pass. 

May 19th, 2021 – Bootcamp Warmup – Data Literacy

June 2nd, 2021 – Bootcamp Warmup – AI Literacy

Kickstart Bootcamp Day 1 - Introductory sessions (June 8th)

Current sessions include:

  • Introduction to Data Science
  • NLP Fundamentals
  • Bayesian Data Science: Probabilistic Programming
  • Basic Python for Data Processing
  • PyTorch 101: Building a Model Step-by-Step
  • Hands-on RL in Finance: Playing Atari vs Playing Markets
  • Machine Learning For Remote Sensing Based Landcover Change Detection
  • Explainable Artificial Intelligence Explained
  • Teaching Machines to Talk: Modern Speech Synthesis with Deep Learning

Kickstart Bootcamp Day 2 - Introductory to Advanced Sessions (June 9th)

Current sessions include:

  • Hands-on Machine Learning Engineer with scikit-learn
  • Dataframes.jl: a Perfect Sidekick for Your Next Data Science Project
  • Adversarial Attacks and Defence in Computer Vision 101
  • Mastering Gradient Boosting with CatBoost
  • Reproducible and Automated Report Generation
  • Automated Machine Learning with Python – from scikit-learn to auto-sklearn
  • Automatic and Explainable Machine Learning with H2O
  • Federated Learning: Practice and Modern Algorithms
  • MLOps Orchestration: Your Highway to Accelerating Deployment of AI

Kickstart Bootcamp Day 3 - Introductory to Advanced Sessions (June 10th)

Current sessions include:

  • Advanced NLP: From Essentials to Deep Transfer Learning
  • Audio-Visual Speech Enhancement and Separation Based on Deep Learning
  • How to Build and Test a Trading Strategy Using ML
  • Introduction to Data Analysis Using Pandas
  • AI Risk to Companies
  • Responsible Data Science Using Bias-Dashboards
  • Federated Learning from Scratch to Production with Scaleout
  • Advances in Conversational AI and NLP through Large Scale Language Models such as GPT-3

Machine Learning Certification & More

  • Obtain an ODSC Bootcamp Certification of Completion
  • Join Ai+ Training
  • Complete the additional courses and exam to become Machine Learning Certified

Some Current ODSC Europe Instructors

CEOPyMC Labs

Thomas Wiecki, PhD

Thomas Wiecki is the Chief Executive Officer at PyMC Labs (www.pymc-labs.io), the world’s first Bayesian consultancy. Prior to that Thomas was the VP of Data Science at Quantopian, where he used probabilistic programming and machine learning to help build the world’s first crowdsourced hedge fund. He is an author of the popular PyMC3 package — a probabilistic programming framework written in Python. He holds a PhD from Brown University.

Bayesian Modeling without the Math(Track Keynote)

Software Engineer, Core DeveloperInria, Scikit-learn

Olivier Grisel

Olivier Grisel is a machine learning engineer at Inria. He is a member of the team of maintainers of the scikit-learn project. Scikit-learn is an Open Source machine learning library written in Python. His work is supported by the Fondation Inria and its partners.

Hands-on Machine Learning Engineer with scikit-learn(Full-Day Training)

Marie Skłodowska-Curie Research FellowUniversity of Munich

Julia Schulte-Cloos, PhD

Julia Schulte-Cloos is a Marie Skłodowska-Curie funded LMU Research Fellow at the Geschwister Scholl Institute of Political Science at LMU Munich. Her main research interests lie in comparative politics, political behavior, research methodology, and reproducibility. Julia Schulte-Cloos has earned her PhD from the European University Institute.

Research ScientistBosch Center for AI

Daria Stepanova, PhD

Daria Stepanova is a research scientist at Bosch Center for Artificial Intelligence. Her research interests include Knowledge Representation and Reasoning with a special focus on the automatic acquisition of rules from structured knowledge. Previously Daria was a senior researcher at Max Plank Institute for Informatics (Germany), where she was heading a group on Semantic Data. Daria got her diploma degree in Applied Computer Science from the Department of Mathematics and Mechanics of St. Petersburg State University (Russia) in 2010 and a PhD in Computational Logic from Vienna University of Technology (Austria) in 2015. Before starting her PhD she worked as a visiting researcher at the School of Computing Science at Newcastle University (UK) in an industrially-oriented project.

Rule Induction and Reasoning in Knowledge Graphs(Tutorial)

Professor Of Computer Science | University of FreiburgUniversity of Freiburg

Frank Hutter, PhD

Frank Hutter is a Full Professor for Machine Learning at the Computer Science Department of the University of Freiburg (Germany), as well as Chief Expert AutoML at the Bosch Center for Artificial Intelligence.
Frank holds a PhD from the University of British Columbia (UBC, 2009) and a Diplom (eq. MSc) from TU Darmstadt (2004). He received the 2010 CAIAC doctoral dissertation award for the best thesis in AI in Canada, and with his coauthors, several best paper awards and prizes in international competitions on machine learning, SAT solving, and AI planning. He is the recipient of a 2013 Emmy Noether Fellowship, a 2016 ERC Starting Grant, a 2018 Google Faculty Research Award, a 2020 ERC PoC Award, and he is a Fellow of ELLIS. Frank’s recent research focuses on automated machine learning (AutoML), where he co-organized the ICML workshop series on AutoML every year since its inception in 2014, co-authored the prominent AutoML tools Auto-WEKA, Auto-sklearn, and Auto-PyTorch, won the first two AutoML challenges with his team, co-authored the first book on AutoML, worked extensively on efficient hyperparameter optimization and neural architecture search, and gave a NeurIPS 2018 tutorial with over 3000 attendees.

Evolution of Efficient and Robust AutoML Systems(Talk)

Research EngineerCloudera Fast Forward Labs

Nisha Muktewar

Nisha Muktewar is a Research Engineer at Cloudera Fast Forward Labs, where she spends time researching latest ideas in machine learning, builds prototypes that showcase these capabilities when applied to real-world use cases, and advises clients in this space. Prior to joining Cloudera, she worked as a Manager in Deloitte’s Actuarial & Modeling practice leading teams in designing, building, and implementing predictive modeling solutions for pricing, consumer behavior, marketing mix, and customer segmentation use cases for insurance and retail/consumer businesses.

Meta-Learning: Learning to Learn(Talk)

David Talby: NLP for healthcare
CTOJohn Snow Labs

David Talby, PhD

David Talby is a chief technology officer at Pacific AI, helping fast-growing companies apply big data and data science techniques to solve real-world problems in healthcare, life science, and related fields. David has extensive experience in building and operating web-scale data science and business platforms, as well as building world-class, Agile, distributed teams. Previously, he was with Microsoft’s Bing Group, where he led business operations for Bing Shopping in the US and Europe and worked at Amazon both in Seattle and the UK, where he built and ran distributed teams that helped scale Amazon’s financial systems. David holds a Ph.D. in computer science and master’s degrees in both computer science and business administration.

Model Governance: A Checklist for Getting AI Safely to Production(Talk)

AI Product ManagerScaleway

Olga Petrova, PhD

A former theoretical physicist turned machine learning engineer, Olga is now building a smart data annotation platform at Scaleway as a technical product manager. On the community side, she enjoys blogging about the latest advancements in AI both in and out of working hours. Some of her writing can be seen on medium.com/@olgapetrova_92798.

Introduction to Transformers for NLP: Where We Are and How We Got Here(Tutorial)

Manager, Financial Advisory Analytics, DeanDeloitte, Data Science Retreat

Daniel Voigt Godoy

Daniel is a data scientist, teacher, and author of “Deep Learning with PyTorch Step-by-Step: A Beginner’s Guide”.
He has been teaching machine learning and distributed computing technologies at Data Science Retreat, the longest-running Berlin-based bootcamp, since 2016, helping more than 150 students advance their careers. Daniel is also the main contributor of two Python packages: HandySpark and DeepReplay.
His professional background includes 20 years of experience working for companies in several industries: banking, government, fintech, retail, and mobility.

PyTorch 101: Building a Model Step-by-Step(Workshop)

Co-founder, CTOPeg

Alex Peattie

Alex Peattie is the co-founder and CTO of Peg, a technology platform helping multinational brands and agencies to find and work with top YouTubers. Peg is used by over 1500 organisations worldwide including Coca-Cola, L’Oreal and Google.

An experienced digital entrepreneur, Alex spent six years as a developer and consultant for the likes of Grubwithus, Huckberry, UNICEF and Nike, before joining coding bootcamp Makers Academy as senior coach, where he trained hundreds of junior developers. Alex was also a technical judge at this year’s TechCrunch Disrupt conference.

Teaching Machines to Talk: Modern Speech Synthesis with Deep Learning(Workshop)

Senior Data Scientist | LecturerInPost | Wrocław University of Economics and Business

Marta Markiewicz

Currently Senior (Big) Data Scientist at InPost and Lecturer at Wroclaw University of Economics and Business, previously Head of Data Science at Objectivity, with background in Mathematical Statistics. For almost 10 years, she has been discovering the potential of data in various business domains, from medical data, through retail, HR, finance, aviation, real estate, logistics, … She deeply believes in the power of data in every area of life. Articles’ writer, conference speaker and privately – passionate dancer and hand-made jewellery creator.

The Colours of Cleaning(Talk)

Founder & Lead Data ScientistApplied Artificial Intelligence

Stefan Jansen

Stefan is the founder and Lead Data Scientist at Applied AI. He advises Fortune 500 companies, investment firms and startups across industries on data & AI strategy, building data science teams, and developing machine learning solutions. Before his current venture, he was a partner and managing director at an international investment firm where he built the predictive analytics and investment research practice. He also was a senior executive at a global fintech company with operations in 15 markets.
Earlier, he advised Central Banks in emerging markets, worked for the World Bank, raised $35m from the Gates Foundation to cofound the Alliance for Financial Inclusion, and has worked in six languages across Asia, Africa, and Latin America. Stefan holds Master degrees in Computer Science from Georgia Tech and in Economics from Harvard and Free University Berlin and is a CFA Charterholder. He is the author for ‘Machine Learning for Algorithmic Trading’ and has been teaching data science at Datacamp and General Assembly.

How to Build and Test a Trading Strategy Using ML(Half-Day Training)

Associate Director – Business Tech Analysis, IT & AIMSD

Guglielmo Iozzia

Guglielmo is part of MSD (Merck & Co. in North America). He is currently busy unlocking business value through Computer Vision and other ML/DL/AI applications to the biotech manufacturing space. He has an extensive background in Software Engineering and Data Science across other big organizations including IBM, Optum and FAO of the UN in diverse contexts (such as Healthcare, DevOps, Cyber Security). Guglielmo has been recognized as DataOps Champion at the Streamsets DataOps Summit 2019 and awarded as one of the Top 50 Tech Visionaries at the 2019 Dubai Intercon Conference. Since 2018 he is also an international speaker (almost 30 international conferences so far, including Big Things 2019 and 2020, Spark+AI Summit 2019, Annual Cyber Security and AI Summit 2019 and 2020), author of a tech book on distributed Deep Learning with Apache Spark and planning about a second tech book which should be probably released at the end of 2021.

Adversarial Attacks and Defence in Computer Vision 101(Workshop)

Kubernetes Contributor and CNCF Ambassador | Founder & CEOWeaveworks | luxas Labs Ltd.

Lucas Käldström

Lucas is a cloud native expert who’s serving the CNCF community in lead positions for 5 years. He’s awarded Top CNCF Ambassador 2017 with Sarah Novotny. Lucas was a co-lead for SIG Cluster Lifecycle, co-created kubeadm, Cluster API & Weave Ignite and ported Kubernetes to ARM. Lucas runs 3 meetups, and has spoken at 7 KubeCons. Most recently, Lucas co-created Racklet besides his university studies.

Exploring Modern and Secure Operations of Kubernetes Clusters on the Edge(Talk)

Senior Research Associate in Biomedical Data Science and University Research LecturerUniversity of Oxford

Sara Khalid

Sara is a Senior Research Associate in Biomedical Data Science and University Research Lecturer at the University of Oxford, where she is the Machine Learning Lead in the Centre for Statistics in Medicine. She has 12 years of experience in machine learning, signal processing, and intelligent remote monitoring research, with applications in biomedical and planetary health informatics. Sara has served on the NASA Frontier Development Lab Artificial Intelligence Panel and the NASA Climate Challenge Big Think. She is a National Geographic Society Explorer in Tracking Plastic Pollution with Remote Monitoring and Machine Learning. Sara is also a University of Oxford Ambassador for Women in Data Science.

DirectorNeuron Labs

Alex Honchar

Alex Honchar is a tech entrepreneur and educator. Currently, he is co-founder and ML director at Neurons Lab – a consulting firm specializing in healthcare, finance, and IoT. Also, he writes a popular blog on Medium about machine learning applications and leadership. Previously he worked as an independent consultant with SMBs and startups on rapid go-to-market ML solutions and taught machine learning courses at the University of Verona and Ukrainian Catholic University.

Research Staff MemberIBM Research and MIT-IBM Watson AI Lab

Mikhail Yurochkin, PhD

Mikhail is a Research Staff Member at IBM Research and MIT-IBM Watson AI Lab in Cambridge, Massachusetts. His research interests are Model fusion and federated learning; Algorithmic fairness; Applications of optimal transport in machine learning; Bayesian (nonparametric) modeling and inference. Before joining IBM, he completed Ph.D. in Statistics at the University of Michigan, where he worked with Long Nguyen. He received his bachelor’s degree in applied mathematics and physics from the Moscow Institute of Physics and Technology.

Data Scientist, Software Engineer, Author of Hands-On Data Analysis with PandasBloomberg

Stefanie Molin

Stefanie Molin is a data scientist and software engineer at Bloomberg in New York City, where she tackles tough problems in information security, particularly those revolving around anomaly detection, building tools for gathering data, and knowledge sharing. She is also the author of “Hands-On Data Analysis with Pandas,” which is currently on in its second edition. She holds a bachelor’s of science degree in operations research from Columbia University’s Fu Foundation School of Engineering and Applied Science. She is currently pursuing a master’s degree in computer science, with a specialization in machine learning, from Georgia Tech. In her free time, she enjoys traveling the world, inventing new recipes, and learning new languages spoken among both people and computers.

Introduction to Data Analysis Using Pandas(Half-Day Training)

Head Big Data FoundationsSwiss Re

Lukáš Csóka

Lukas Csoka, working as Head Big Data Foundations in Swiss Re, one of the biggest global reinsurers, combines data science, consultative thinking and business partnering as the main skills used daily in his job to push design and develop new AI products. His MS in software engineering from Slovak University of Technology and MBA in global management from City University of Seattle are supporting him during this journey. His projects include innovative solutions for farmers using satellites, the application of predictive methods to manage costs inside Swiss Re or the analysis of thousands of client meetings from text and the provision of recommendations to Swiss Re’s traders and many others.

AI Risk to Companies(Workshop)


Bootcamp Experience

What You’ll Learn

 Learn Fundamentals

Prepare for your immersive training by learning core fundamentals during our pre-bootcamp sessions in the summer, including:

  • Fundamentals of Python Programming

  • Data Analysis in Python

  • Mathematics for Data Science

  • Introduction to Statistics for Data Science

  • SQL for Data Science and Engineering

Learn Frameworks & Tools

Get hands-on experience with in-demand data science tools and frameworks, including:

  • Python, Jupyter Notebooks

  • R programming, Julia, Scala, Stan

  • Apache Spark, MLlib, Streaming

  • Tensorflow, MXNet, Caffe, CNTK

  • Scikit-learn, Theano, Shogun, Pylearn2

  • See schedule for many more…

Learn Core Topics

Get hands-on experience in the most important data science topics with over 40 beginner to intermediate sessions to choose from, including

  • Deep Learning with Tensorflow and Keras

  • Reinforcement Learning and Deep Reinforcement Learning

  • Machine Learning

  • Transfer Learning

  • Natural Language Processing

  • Text Analytics

  • Data Visualization and Storytelling

  • Data Modeling and Data Wrangaling

  • NLP BERT and Pre-trained models

  Build your Network

A career in data science opens up the possibility of rewarding and exciting work. Build your network and help grow your career

  • Learn from and connect with world-leading data science experts

  • Stop by our Career Expo and meet top hiring companies like Google, DataRobot, and dozens of others

  • Join our various virtual networking events, such as Meet the Speakers, Meet the Experts, Ignite session; and many more

  • Network with hundreds of data science attendees to learn what it’s like to be a data scientist

Registration

10% off ends in:


Choose your Pass

Access to ODSC Europe 2020 recordigs

Pre-Conference On Demand or Live Training

1 Year of AI+ Training Premium Subscription

Tuesday - Thursday |  ODSC Workshops 

Tuesday - Thursday | ODSC Training Sessions

Tuesday - Thursday | ODSC Talks - 30 Sessions

Wednesday & Thursday | Virtual AI Expo and Demo Talks

Tuesday | Virtual Career Expo 

On-demand Access to All Conference recordings

All Access

€399


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Kickstart Bootcamp

€659


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Companies represented at ODSC Bootcamp

Open Data Science

Open Data Science
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101 Main St
Cambridge, MA 02142
info@odsc.com

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