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Kick-start your career in data science in 3 immersive days. Get the skills you need, taught by world-renowned expertsÂ
WHY an ODSC BOOTCAMP?
Start Early
With Prerequisites training, you can start learning the very fundamentals of data science. Learn how to code with Python and SQL, basic match skills and any other preques you need
 3-day Immersive
Join the 3-day live Mini-Bootcamp onsite or virtually
Get Certified
Join Ai+ Training and complete your Machine Learning certification
Get HelpÂ
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
Specialization Tracks
Machine Learning with Python
- Mathematics for Data Science
- Programming with Data: Python and Pandas
- Hands-on Machine Learning with scikit-learn
- Machine Learning at Scale using Apache Spark
- Supervised Learning for Missing Data
- Causal Inference for Data Science
- Meta-learning for Machine Learning
- Cybersecurity in ML
- Reinforcement Learning with TF-Agents
- Reinforcement Learning for Human Language
Deep Learning
- Intro to Neural Networks for Deep Learning
- PyTorch Hands-on Training
- Deep Reinforcement Learning
- Deep Learning with Tensorflow
- Recommendation Systems with Deep Learning
- Deep Learning with Keras
- TFF (Tensorflow Federated Learning)
- How to Identify Deepfakes
- Deep Learning CNNs and GANs
Data Engineering / MLOps
- Mathematics for Data Science
- SQL for Data Science
- Deploying ML Pipelines with Open-data
- Kubeflow & Kubernetes
- Auto Machine Learning
- Debugging Machine Learning
- Introducing Flyte
- Reproducible Data Science in Pachyderm
- Data Science Best Practices: Continuous Delivery for Machine Learning
NLP
- Introduction to NLP and Topic Modeling
- Transfer Learning in NLP
- Training NLP Models with Deep Reinforcement Learning
- State-of-the-Art NLP in TensorFlow and PyTorch
- Active Learning for Data Labeling
- NLP with LSTMs (Deep learning)
- Using HuggingFace Transformers for NLP
Data Analytics
- Statistics and Probability Distribution
- Big Data using Spark
- Streaming Analytics
- Augmented Analytics
- Decision Analytics
- Graph Analytics
- No-Sql
- In-memory computing
Live sessions include, but are not limited to, the ones listed below.
Dive Deeper
Get hands-on experience in job-ready skills
Registration
10% off ends in:
 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 Virtual Mini-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.
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 Đšimworld 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.
Europe 2022 Mini-Bootcamp 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.
- Complete Python Fundamentals – by Mona Khalil (Duration: ~4 hrs)
- Modern Data Acquisition using Python – by Max Humber, General Assembly (Duration: ~2 hrs)
- Data Science 101: Machine Learning & Modeling in Theory & Practice – by Kirk Borne, PhD, Booz Allen Hamilton (Duration: ~4 hrs)
- SQL for Data Science – by Mona Khalil, Greenhouse Software (Duration: ~3 hrs)
- Recommendation Systems in Python – by Joshua Bernhard, NerdWallet (Duration: ~3 hrs)
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:
-
- March 15th 2022 ODSC East Bootcamp Warmup: AI Literacy
- March 16th 2022 Deep Learning Bootcamp
- March 23rd 2022 Complete Business Intelligence BI with Python Data Science
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.
Mini-Bootcamp Day 0 - Introductory sessions (June 14th)
Current sessions include:
- Introduction to Python for Data Analysis
- Introduction to Machine Learning
- Introduction to Linear Algebra for Data Science and Machine Learning With Python
Mini-Bootcamp Day 1 - Introductory to Advanced Sessions (June 15th)
Current sessions include:
- Hands-on Machine Learning Engineer with scikit-learn
- NLP Fundamentals
- GPU Development with Python 101
- PyTorch 101: Building a Model Step-by-step
- Visually Inspecting Data Profiles for Data Distribution Shifts
- Next-Generation Web Apps: Create a Machine Learning Powered Smart Cam in the Browser with TensorFlow.js
- Revealing the Inner Self: Automatic Differentiation (Autodiff) Clearly Explained
Mini-Bootcamp Day 2 - Introductory to Advanced Sessions (June 16th)
Current sessions include:
- Advanced NLP: Deep Learning and Transfer Learning for Natural Language Processing
- Time-Series in Python – Preprocessing and Machine Learning
- GANs N’ Roses: Understanding Generative Models
- Hearing is Believing: Generating Realistic Speech with Deep Learning
- Diffusion Models for Text-to-Image Generation
- A Dive into Delta Lake: A Modern File Format for the Next-Generation Lake
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
Choose your Pass
Tuesday | Virtual Mini-Bootcamp Training Sessions
Premium 1-Year Subscription to AI+ Training (value = $700)
Access to All Virtual Sessions & Events (Tue-Thu)
ODSC Keynotes & Talks (Wed-Thu)
Prep Training: live and On-demand (value = $499)
On-demand Access to All Conference recordings
Access to AI Solution Showcase Expo Area (Wed-Thu)
Access to ODSC In-Person Workshops & Training Sessions (Wed&Thu)
Access to In-person Mini-Bootcamp Training Sessions
Bootcamp Experience
Virtual Experience
In-Person Experience
Learn from the Best
Our mission is to provide you with applied training from some of the top instructors in the field. Confirmed ODSC Europe instructors Coming Soon:
Andrea Lowe, PhD
Andrea Lowe, PhD is the Training and Enablement Engineer at Domino Data Labs where she develops training on topics including overviews of coding in Python, machine learning, Kubernetes, and AWS. She trained over 1000 data scientists and analysts in the last year. She has previously taught courses including Numerical Methods and Data Analytics & Visualization at the University of South Florida and UC Berkeley Extension. Her conference experience includes a deep learning tutorial at PyCon, 2 invited talks, 21 poster presentations, and 4 chair positions.
Practical Reinforcement Learning for Data Scientists(Workshop)
Jennifer Dawn Davis, PhD
Jennifer Davis, Ph.D. is a Staff Field Data Scientist at Domino Data Labs, where she empowers clients on complex data science projects. She has completed two postdocs in computational and systems biology, trained at a supercomputing center at the University of Texas, Austin, and worked on hundreds of consulting projects with companies ranging from start-ups to the Fortune 100. Jennifer has previously presented topics at conferences for Association for Computing Machinery on LSTMs and Natural Language Generation and at conferences across the US and in Italy. Jennifer was part of a panel discussion for an IEEE conference on artificial intelligence in biology and medicine. She has practical experience teaching both corporate classes and at the college level. Jennifer enjoys working with clients and helping them achieve their goals.
Large Scale Deep Learning using the High-Performance Computing Library OpenMPI and DeepSpeed(Workshop)
Daniel Gerlanc
Daniel Gerlanc has worked as a data scientist for more than decade and been writing software for nearly 20 years. He frequently teaches live trainings on oreilly.com and is the author of the video course Programming with Data: Python and Pandas. He has coauthored several open source R packages, published in peer-reviewed journals, and is a graduate of Williams College.
Programming with Data: Python and Pandas(Training)
Boris Paskhaver
Boris Paskhaver is a full-stack web developer based in New York City with experience building apps in React / Redux and Ruby on Rails. His favorite part of programming is the never-ending sense that there’s always something new to master — a secret language feature, a popular design pattern, an emerging library or — most importantly — a different way of looking at a problem.
Getting Started with Pandas for Data Analysis(Half-Day Training)
Clinton Brownley, PhD
Clinton Brownley, Ph.D., is a data scientist at Meta (formerly Facebook), where he’s responsible for a variety of analytics projects designed to empower employees to do their best work. Prior to this role, he was a data scientist at WhatsApp, working to improve messaging and VoIP calling performance and reliability. Before WhatsApp, he worked on large-scale infrastructure analytics projects to inform hardware acquisition, maintenance, and data center operations decisions at Facebook.
As an avid student and teacher of modern data analysis and visualization techniques, Clinton teaches a graduate course in interactive data visualization for UC Berkeley’s MIDS program, taught a short-term graduate course in regression analysis and machine learning workshop for NYU’s A3SR program, leads an annual machine learning in Python workshop, and is the author of two books, “Foundations for Analytics with Python” and “Multi-objective Decision Analysis”.
Clinton is a past-president of the San Francisco Bay Area Chapter of the American Statistical Association and is a council member for the Section on Practice of the Institute for Operations Research and the Management Sciences. Clinton received degrees from Carnegie Mellon University and American University.
Machine Learning with Python: A Hands-On Introduction(Training)
Noemi Derzsy, PhD
Noemi Derzsy is a Senior Inventive Scientist at AT&T Chief Data Office within the Data Science and AI Research organization. Her research is centered on understanding and modeling customer behavior and experience through large-scale consumer and network data, using machine learning, network analysis/modeling, Spatio-temporal mining, text mining, and natural language processing techniques.
Prior to joining AT&T, Noemi was a Data Science Fellow at Insight Data Science NYC and a postdoctoral research associate at Social Cognitive Networks Academic Research Center at Rensselaer Polytechnic Institute. She holds a Ph.D. in Physics, MS in Computational Physics, and has a research background in Network Science and Computer Science.
Noemi is also involved in volunteering in the data science community. She is a NASA Datanaut and former organizer of the Data Umbrella meetup group and NYC Women in Machine Learning and Data Science meetup group.
Exploring the Interconnected World: Network/Graph Analysis in Python(Tutorial)
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 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.
Matt Brems
Matt currently leads instruction for GA’s Data Science Immersive in Washington, D.C. and most enjoys bridging the gap between theoretical statistics and real-world insights. Matt is a recovering politico, having worked as a data scientist for a political consulting firm through the 2016 election. Prior to his work in politics, he earned his Master’s degree in statistics from The Ohio State University. Matt is passionate about making data science more accessible and putting the revolutionary power of machine learning into the hands of as many people as possible. When he isn’t teaching, he’s thinking about how to be a better teacher, falling asleep to Netflix, and/or cuddling with his pug.
Good, Fast, Cheap: How to do Data Science with Missing Data(Half-Day Training)
On-Demand Post Conference Training Â
With Each ODSC Bootcamp pass, you get a 1 year Ai+ on-demand hands-on training subscription (Value $700)
Ai+ is the only hands-on training platform solely developed for AI practitioners. Keep training with the top names in the industry. Free for 1 year with an ODSC Europe Bootcamp pass.
What You’ll Learn
 Learn Fundamentals
Prep for your immersive training by learning core fundamentals, including:
Fundamentals of Python Programming
Data Analysis in Python
Introduction to Statistics for Data Science
Fundamental Analytics for Data 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
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
Reinforcement Learning and Deep Reinforcement Learning
Machine Learning
Transfer Learning
Natural Language Processing
Text Analytics
Data Visualization
Data Modeling and Data Wrangling
 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 networking events, such as Meet the Speakers, Meet the Experts, Dinner with Data Scientists; plus other networking opportunities
Network with hundreds of data science attendees to learn what it’s like to be a data scientist
Some of Our Featured ODSC Europe Instructors
Hadrien Jean, PhD
Hadrien Jean is a machine learning scientist working at My Medical Assistent where he is developing deep learning models in the medical domain. He wrote the book Essential Math for Data Science (https://www.essentialmathfordatascience.com/) aimed at helping people to get the math needed in data science from a coding perspective. He previously worked at Ava on speech diarization. He also worked on a bird detection project using deep learning. He completed his Ph.D. in cognitive science at the École Normale Supérieure (Paris, France) on the topic of auditory perceptual learning with a behavioral and electrophysiological approach. He has published a series of blog articles aiming at building intuition on mathematics through code and visualization (https://hadrienj.github.io/posts/).
Introduction to Linear Algebra for Data Science and Machine Learning With Python(Bootcamp)
Julia Lintern
Julia Lintern currently works as an instructor for the Metis Data Science Flex Program. Previously, she worked as a Data Scientist for the New York Times. Julia began her career as a structures engineer designing repairs for damaged aircraft. Julia holds an MA in applied math from Hunter College, where she focused on visualizations of various numerical methods and discovered a deep appreciation for the combination of mathematics and visualizations. During certain seasons of her career, she has also worked on creative side projects such as Lia Lintern, her own fashion label.
Introduction to Machine Learning (Bootcamp)
Leonidas Souliotis, PhD
Leonidas (Leo) is a Senior Data Scientist at Astrazeneca. His work is focused around machine learning in oncology, including clinical and non clinical applications. He is also enthusiastic about NLP applications in oncology and how this can be used to leverage patient treatment. He is also a workshop facilitator in the European Leadership University (ELU), NL and has also been a data science educator at DataCamp. He holds a PhD from the University of Warwick, UK. in bioinformatics and ML, an MSc in statistics from Imperial College London, UK and a BSc in Statistics and Insurance Science from the University of Piraeus, GR.
Introduction to Python for Data Analysis(Bootcamp)
Laurence Moroney
Laurence Moroney leads AI Advocacy at Google, working with the Google AI Research and product development teams. He’s the best-selling author of ‘AI and Machine Learning for Coders,’ as well as the instructor on the Fundamentals of TinyML course at HarvardX, and the popular TensorFlow specializations with deeplearning.ai and Coursera. He’s passionate about empowering software developers to succeed in Machine Learning, democratizing AI as a result. Laurence is based on Washington State in the USA.
A Hands-on Guide to Machine Learning with TensorFlow(Tutorial)
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.
Hearing is Believing: Generating Realistic Speech with Deep Learning(Workshop)
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 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.
Adrin Jalali, PhD
He is a computer scientist / bioinformatician who has turned to be a core developer of `scikit-learn` and `fairlearn`, and work as a Machine Learning Engineer at Hugging Face. He is also an organizer of PyData Berlin.
These days he mostly focus on aspects of machine learning and tools which help with creating more ethical and fair decision making systems. This trend has influenced him to work on `fairlearn`, and to work on aspects of `scikit-learn` which would help tools such as `fairlearn` to work more fluently with the package; and at Hugging Face, his focus is to enable the community of these libraries to be able to share their models more easily and be more open about their work.
Dipanjan (DJ) Sarkar
Dipanjan (DJ) Sarkar is a data science consultant and published author, and was recognized as a Google Developer Expert in Machine Learning by Google in 2019. He currently works as a lead data science consultant at Schaffhausen Institute of Technology Academy, Zurich. Dipanjan has led advanced analytics initiatives working with Fortune 500 companies like Intel, Applied Materials, Red Hat / IBM. He works on leveraging data science, machine learning and deep learning to build large- scale intelligent systems. Dipanjan also works as an independent consultant, mentor and AI advisor in his spare time collaborating with multiple universities, organizations and startups across the globe. His passion includes solving challenging data problems as well as educating and helping people upskill in all things data. Dipanjan has also been recognized as one of the top ten Data Scientists in India in 2020, 40 under 40 Data Scientists, 2021 and Top 50 AI Thought Leaders by Global AI Hub, Switzerland. In his spare time he loves reading, gaming, watching interesting documentaries, football. He is also a strong supporter of open-source and publishes his code and analyses from his books, articles and experience on GitHub at https://github.com/dipanjanS and LinkedIn at https://www.linkedin.com/in/dipanzan
Advanced NLP: Deep Learning and Transfer Learning for Natural Language Processing(Workshop)
Leonardo De Marchi
Leonardo De Marchi holds a Master in Artificial intelligence and has worked as a Data Scientist in the sports world, with clients such as the New York Knicks. He now works in Thomson Reuters as VP of Labs, and also provides consultancy and training for small and large companies. His previous experience includes being Head of Data Science and Analytics in Bumble, the largest dating site with over 500 million users, heading the team through acquisition and an IPO.
NLP Fundamentals(Training)
Jared Lander
Jared Lander is the Chief Data Scientist of Lander Analytics a data science consultancy based in New York City, the Organizer of the New York Open Statistical Programming Meetup and the New York R Conference and an Adjunct Professor of Statistics at Columbia University. With a masters from Columbia University in statistics and bachelors from Muhlenberg College in mathematics, he has experience in both academic research and industry. His work for both large and small organizations ranges from music and fundraising to finance and humanitarian relief efforts. He specializes in data management, multilevel models, machine learning, generalized linear models, data management and statistical computing. He is the author of R for Everyone: Advanced Analytics and Graphics, a book about R Programming geared toward Data Scientists and Non-Statisticians alike and is creating a course on glmnet with DataCamp.
Dr. Colin Gillespie
Dr Colin Gillespie is the Co-Founder and CTO of Jumping Rivers. A data science consultancy that specialises in all things R and Python. He is also a Senior Statistics lecturer at Newcastle University, has published over eighty peer-reviewed papers, and co-authored the O’Reilly book, Efficient R programming.
Oliver Zeigermann
Oliver is a software developer from Hamburg Germany and has been a practitioner for more than 3 decades. He specializes in frontend development and machine learning. He is the author of many video courses and textbooks.
Image Recognition with OpenCV and TensorFlow(Training)
Jacob Tomlinson
Jacob Tomlinson is a senior Python software engineer at NVIDIA with a focus on deployment tooling for distributed systems. His work involves maintaining open source projects including RAPIDS and Dask. RAPIDS is a suite of GPU accelerated open source Python tools which mimic APIs from the PyData stack including those of Numpy, Pandas and SciKit-Learn. Dask provides advanced parallelism for analytics with out-of-core computation, lazy evaluation and distributed execution of the PyData stack. He also tinkers with the open source chatbot automation framework Opsdroid in his spare time. Jacob volunteers with the local tech community group Tech Exeter and lives in Exeter, UK.
GPU Development with Python 101(Workshop)
Daniel Voigt Godoy
Daniel has been teaching machine learning and distributed computing technologies at Data Science Retreat, the longest-running Berlin-based bootcamp, for more than three years, helping more than 150 students advance their careers. He writes regularly for Towards Data Science. His blog post “Understanding PyTorch with an example: a step-by-step tutorial” reached more than 220,000 views since it was published. The positive feedback from the readers motivated him to write the book Deep Learning with PyTorch Step-by-Step, which covers a broader range of topics.
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.
Ryan Dawson
Ryan Dawson is a technologist passionate about data. Ryan works with clients on large-scale data and AI initiatives, helping organizations get more value from data. His work includes strategies to productionize machine learning, organizing the way data is captured and shared, selecting the right data technologies and optimal team structures, as well as writing the code to make it happen. He has over 15 years of experience and, as well as many widely read articles about MLOps, software design, and delivery. is author of the Thoughtworks Guide to Evaluating MLOps Platforms.
Data Mesh: From Concept to Code(Talk)
Data Science in the Industry: Continuous Delivery for Machine Learning(Training)
Learn More About Our Program
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
Companies represented at ODSC Bootcamp
ODSC Newsletter
Stay current with the latest news and updates in open source data science. In addition, we’ll inform you about our many upcoming Virtual and in person events in Boston, NYC, Sao Paulo, San Francisco, and London. And keep a lookout for special discount codes, only available to our newsletter subscribers!