ODSC Team Training
Onsite and Offsite Training in Data Science and Artificial Intelligence
♦ ODSC East 2021 Virtual Training → Mar 30th to April 1st
Our ability to learn what we need for tomorrow is more important than what we know today
George Siemens
Key Reasons to Send Your Team to ODSC
Upskill Your Team
3 days of learning and work-enhancing experiences with the latest languages, tools, frameworks, and models in Data Science.
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Sessions presented by some of the top instructors and practitioners in the AI space.
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Certificate of Completion after completing a post-event assessment.
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The skills and knowledge acquired have immediate impact in your organization. Instant ROI
Encourage Innovation
Training presents a prime opportunity to expand the knowledge base of all employees.
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Propel your team out of its comfort zone; training and upskilling encourages new ideas.
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Investing time and money shows employees they are being valued.
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Build a strong company reputation by focusing on employee development. Keep the talent and reduce employee turnover.
Introduce Networked Learning
ODSC stands by the concept of Networked Learning, learning based on the idea of networks and connectivity.
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Join the fastest growing network of AI practitioners, sharing knowledge, projects, failures…
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Team bonding through learning together, interacting with thought leaders and peers, along with a bit of fun.
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Learning and knowledge rests in diversity of opinions.
ODSC East Previous Instructors & Speakers
Confirmed Sessions
Training & Workshops
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Tutorial: Managing the Complete Machine Learning Lifecycle with MLflow
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Data Science and Machine Learning in the Cloud for Cloud Novices
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Time Series Analysis: From Introduction to Advanced Topics
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Introduction to Machine Learning with R
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Custom Data Visualizations with Python
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Uplift Modeling Tutorial: Predictive and Prescriptive Analytics
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Advanced Machine Learning with scikit-learn
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State of the Art Natural Language Processing at Scale
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Learning Python by Cleaning Data in Pandas
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Modern and Old Reinforcement Learning
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Understanding the PyTorch Framework with Applications to Deep Learning
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Deploying Data Science Applications
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Advanced Methods for Working with Missing Data in Supervised Machine Learning
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Solving the Data Scientist’s Dilemma: The Cold-Start Problem with 10+ Machine Learning Examples
