Bengaluru | Aug 7 - 10, 2019

Data Science Kick-start

Kick-Start Your Data Science Career
Register

Learn Essential Skills to Kick-Start Your Career

Data Science skills are in ever-increasing demand. Whether you are beginning your data science career, a software engineer eager to augment your skills, or even a business professional looking beyond the hype, our Kick-start track is for you.

Accelerated Learning Over 4 Packed Days

The Data Science Kick-start track offers many introductory level talks, tutorials, and workshop to get you started. Our expert speakers and presenters offer world-class instruction and provide invaluable insights to help you learn what matters most.  We cover the most important tools, topic, and techniques in use to ensure you are ready to hit the ground running.

  • Machine Learning

  • Deep Learning

  • Artificial Intelligence

  • Neural Networks

  • Natural Language Processing

  • Computer Vision

  • Pattern Recognition

  • R

  • Python SciPy, Pandas, etc

  • Scikit-learn

  • Tensorflow

  • Spark

  • MLlib

  • H20

  • WEKA

  • Pylearn2

  • Theano

  • Caffe

  • Torch

  • Azure Machine Learning API

  • and many more..


Sample of Past Speakers

Andreas Mueller, PhD
Andreas Mueller, PhD

Core Contributor to scikit-learn

Columbia Center for Data Science

Marsal Galvada, PhD
Marsal Galvada, PhD

Head of Machine Learning at Square

Michael Tamir, PhD
Michael Tamir, PhD

Head of Data Science at Uber

Sihem Romdhani
Sihem Romdhani

Software Engineer at Veeva Systems

Victor Lo, PhD
Victor Lo, PhD

Head of Data Science & AI at Fidelity Investments

Maya Gupta, PhD
Maya Gupta, PhD

Glassbox ML R&D Team Lead at Google

Jeffrey Yau, PhD
Jeffrey Yau, PhD

Chief Data Scientist at AB

Michael Segala
Michael Segala

CEO at SFL Scientific

Francesco Mosconi, PhD
Francesco Mosconi, PhD

Data Scientist, Consultant, and Trainer at CATALIT

ODSC India Speakers coming soon
Jose Portilla
Jose Portilla

Head of Data Science at Pierian Data Inc.

Viral Shah, PhD
Viral Shah, PhD

Co-founder, CEO at Julia Computing, Inc.

Joshua Bloom, PhD
Joshua Bloom, PhD

VP Data Analytics at GE

Joshua Gordon
Joshua Gordon

Machine Learning Lead at Google

Here Are Samples of What You’ll Learn

  • Training: A Tour of Machine Learning Algorithms: The Usual Suspects in Some Unusual Applications

  • Training: Turning a Data Science Brain Dump Into Software

  • Training: A Gentle Introduction to Predictive Analytics with R

  • Training: Introduction to Text Analytics Using R

  • Talk: Introduction to Data Science Using R

  • Talk: Intro to Data Visualization

  • Talk: Deep Learning for Absolute Beginners

  • Talk: Intro to Python for Data Science

  • And many more!

What You’ll Learn

Data science has many focus areas.  The goal of this track is to accelerate your knowledge of data science by offering a series of introductory level training sessions, talks, and workshops on the most important tools and topics.

  • Deep Learning

  • Machine Learning

  • Artificial Intelligence

  • Text Analytics

  • Data Wrangling

  • Predictive Analytics

  • Machine Vision

  • Voice AI

  • Pyton for Data Science

  • R & Julia

  • Apache Spark, MLlib

  • Scikit-learn, Azure ML, Amazon ML, H20.ai

  • Tensorflow, Caffe, CNTK, Torch

  • Data Visualization

  • Neo4J, D3.js, R-Shiny

Why Attend?

Immerse yourself in talks, tutorials, and workshops on Machine Learning and Deep Learning tools, topics, models and advanced trends

Expand your network and connect with like- minded attendees to discover how Machine Learning and Deep Learning knowledge can transform not only your data models but also your business and career

Meet and connect with the core contributors and top practitioners in the expanding and exciting field of Machine Learning and Deep Learning

Learn how the rapid rise of intelligent machines is revolutionizing how we make sense of data in the real world and its coming impact on the domains of business, society, healthcare, finance, manufacturing, and more

Sign Up for ODSC India 2019 | Aug 7th - 10th

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