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 YOUR FULL POTENTIAL

Kick-start your career in data science in 3 immersive days. Get the skills you need, taught by world-renowned experts 

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

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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.

Previous Europe 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)

Why wait? Get started immediately in your learning journey with free access to introductory concepts with short, to-the-point, and industry-driven on-demand courses provided by our associated, on-demand training platform: Ai+ Training

Schedule: Self-paced

  • Note: only accessible to Bootcamp registrants and VIP registrations. 
  • Courses provided by Ai+ training and includes a premium subscription
  • Please create a Free Account on Ai+ Training and allow 48 hours from purchase to active Ai+ premium subscription

Pre-Bootcamp Live Training (FREE & PAID)

Get started in your learning track with free access to March to April 2023 LIVE PRE-BOOTCAMP COURSES to learn core concepts from top instructors.  These are held virtually. Currently scheduled training sessions include:

  • March 2, 2023: ODSC Bootcamp Warmup: Data Primer Course
  • March 14,  2023: ODSC Bootcamp Warmup: SQL Primer Course
  • April 6, 2023: ODSC Bootcamp Warmup: Programming Primer Course with Python
  • April 26, 2023: ODSC Bootcamp Warmup: AI Primer Course

Each course is $199 (total $796) Free to Mini-Bootcamp, VIP registrants

Mini-Bootcamp Day 0 - Introductory sessions (June 13th)

These foundation courses include training sessions. The full schedule coming soon. Tentative topics include:

  • Python Fundamentals
  • Introduction to Machine Learning
  • An Introduction to Data Wrangling with SQL

Mini-Bootcamp Day 1 - Introductory to Advanced Sessions (June 14th)

These foundation courses include training sessions, workshops, and tutorials. The full schedule coming soon. Tentative topics include:

  • Introduction to Python for Data Analysis
  • Introduction to Data Science
  • NLP Fundamentals
  • Introduction to Data Analysis Using Pandas
  • sktime – Python Toolbox for Machine Learning with Time Series
  • Generative AI in Practice: How to build your own Stable Diffusion API
  • Hyper-productive NLP with Hugging Face Transformers

Mini-Bootcamp Day 2 - Introductory to Advanced Sessions (June 15th)

These foundation courses include training sessions, workshops, and tutorials. The full schedule coming soon. Tentative topics include:

  • Diffusion Models 101
  • Learn how to Efficiently Build and Operationalize Time Series Models in 2023
  • Introduction to Interpretability in ML (XAI)
  • Automate Machine Learning Workflows with PyCaret 3.0
  • Generative AI

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

Free Pre-Bootcamp Primer Courses

Data, Coding, and AI preparation courses for ODSC Mini-Bootcamps

ODSC Bootcamp Primer Courses

These primer courses can be taken stand alone or as part of our Mini-Bootcamp series. This foundations series is built from the ground up to boost your understanding of data-centric AI

Hosted on Ai+ Training and included FREE as part of your ODSC Mini-Bootcamp Pass. Courses hosted in March and April 2023  On-Demand now

learn more

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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)

4 Prep-Bootcamp Live Tutorials on Data Literacy, AI Literacy, Programming, and SQL (value = $796)

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

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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
Training and Enablement EngineerDomino Data Labs

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)

Staff Field Data ScientistDomino Data Labs

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)

VP of EngineeringNormal Computing

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(Bootcamp)

Software EngineerStride Consulting

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)

Lead Data ScientistTala

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.

Clinton Brownley, Ph.D., is currently a lead data scientist at Tala with a focus on causal inference, machine learning, and experimentation. Prior to this role, he was a data scientist at Meta (formerly Facebook), where he was 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 datacenter 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 and a graduate course in regression analysis for NYU’s A3SR program. He also leads an annual machine learning in python workshop at the ML Week and ODSC West conferences. Clinton is also 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.

Visualization in Bayesian Workflow Using Python or R(Training)

Senior Inventive ScientistAT&T Chief Data Office

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)

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

Stefanie Molin

Stefanie Molin is a software engineer and data scientist at Bloomberg in New York City, where she tackles tough problems in information security, particularly those revolving around data wrangling/visualization, 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, as well as 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.

Managing Partner, Principal Data Scientist | Distinguished FacultyBetaVector | General Assembly

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  
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.

Learn More
Discover Your Bootcamp Learning Path

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

Previous ODSC Europe Instructors

Senior Data ScientistAstraZeneca

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)

Instructor | Principal IC Design EngineerUCLA Extension | Medtronic

Philip Tracton

Phil Tracton is an IC design engineer at Medtronic and an instructor at UCLA Extension. He has worked at Medtronic for over 20 years and has experience in implementing firmware, FPGAs, and custom ASICs. Many thousands of people have his work implanted in them. Most of these devices are focused on Neuromodulation. He has recently joined an internal team focused on long term research for implantable devices.

At UCLA he teaches multiple Python based courses including Learning Python and Python on the Raspberry Pi.

He is interested in low power AI on edge devices.

He will be running the Fundamentals of Python training class. This is his second time teaching at an ODSC event.

Python Fundamentals(Bootcamp)

Director of Data ScienceGartner

Julia Lintern

Julia Lintern currently works as a Director of Data Science at Gartner. 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)

CEO and Software Architect, Data Engineer and AI expertODSC

Sheamus McGovern

Sheamus McGovern is the founder of ODSC (The Open Data Science Conference). He is also a software architect, data engineer, and AI expert. He started his career in finance by building stock and bond trading systems and risk assessment platforms and has worked for numerous financial institutions and quant hedge funds. Over the last decade, Sheamus has consulted with dozens of companies and startups to build leading-edge data-driven applications in finance, healthcare, eCommerce, and venture capital. He holds degrees from Northeastern University, Boston University, Harvard University, and a CQF in Quantitative Finance.

Data Wrangling with Python(Bootcamp)

VP of LabsThomson Reuters

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.

Generative AI(Training)

Manager of Applied ResearchThomson Reuters Labs

Laura Skylaki, PhD

Laura Skylaki is a Manager of Applied Research in Thomson Reuters Labs, where she leads advanced machine learning projects in the domain of Legal and Tax AI.With a career spanning more than a decade at the intersection of research and practical application, she has contributed technical expertise in diverse fields such as bioinformatics and stem cell biology, image processing and natural language processing. She holds a doctorate in stem cell bioinformatics from the University of Edinburgh, UK, and has been publishing on machine learning applications in leading academic journals since 2012.

NLP Fundamentals(Training)

Founder and Core Developer of sktimesktime

Franz Kiraly, PhD

Franz Kiraly is the founder and a core developer of the open source framework sktime. His research is focused on software engineering for open source and data science, machine learning for structured learning tasks such as time series tasks, and robust empirical and statistical evaluation of algorithms in deployment. Franz held a faculty position at University College London 2013-2020, before he moved to industry R&D in principal data scientist roles.

sktime – Python Toolbox for Machine Learning with Time Series(Training)

Data ScientistElectrolux

Marc Rovira, PhD

Marc Rovira is a data scientist at Electrolux Group in Stockholm, with a strong focus on forecasting and time series analysis. He actively contributes to the sktime community as a council member and user representative. Prior to his industry experience, Marc completed a Ph.D. that explored the intersection of computational fluid mechanics, chemical engineering, and machine learning, with the aim of mitigating air pollution. His educational background also includes a master’s degree in aerospace engineering.

sktime – Python Toolbox for Machine Learning with Time Series(Training)

Data Scientist, developer, teacher and writer. Author of "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"

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.

Diffusion Models 101(Workshop)

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

Stefanie Molin

Stefanie Molin is a software engineer and data scientist at Bloomberg in New York City, where she tackles tough problems in information security, particularly those revolving around data wrangling/visualization, 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, as well as 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.

Director of Product, AI Cloud SolutionsGraphcore

Tim Santos

Tim is leading Graphcore’s Cloud Solutions product to help AI & ML software development teams build AI products and deploy ML capabilities in production. Tim has worn many hats in his career, from being a research engineer, data scientist and leading MLOps teams. Along the way, he’s gained experience across all stages of the development lifecycle, taking AI applications from experimentation to deployment.

Generative AI in Practice: How to build your own Stable Diffusion API(Workshop)

Chief EvangelistHugging Face

Julien Simon

Julien is currently Chief Evangelist at Hugging Face. He’s recently spent 6 years at Amazon Web Services where he was the Global Technical Evangelist for AI & Machine Learning. Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering in large-scale startups.


Check more Confirmed Speakers here

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:

Participate at ODSC Europe 2024

Register your interest
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As part of the global data science community we value inclusivity, diversity,  and fairness in the pursuit of knowledge and learning. We seek to deliver a conference agenda, speaker program, and attendee participation that moves the global data science community forward with these shared goals. Learn more on our code of conduct, speaker submissions, or speaker committee pages.

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!


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