Boston | April 30-May 3, 2019

Data Science Kick-start

Kick-start Your Data Science Career

Learn Essential Skills to Kick-start Your Career

Data Science skills are in ever-increasing demand. Whether you are a data science beginner, a software engineer looking to augment 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 workshops to get you started. Our expert speakers and presenters offer world-class instruction, and give you invaluable insights to help you learn what matters most. We cover the most important tools, topics, and techniques in use to ensure you hit the ground running.

Some of Our Current Speakers

Jared Lander

Professor at Columbia Business School

Andreas Mueller, PhD

Author, Research Scientist, Core Contributor of scikit-learn at Columbia Data Science Institute

Lukas Biewald

Founder at Weights & Biases

Jacob Schreiber

PhD Candidate at University of Washington

Todd Cioffi

Data Science Evangelist at DataRobot

Ido Shlomo

Data Science Manager at BlueVine

Ted Kwartler

Director, Data Scientist, Adjunct Professor at Liberty Mutual, Harvard Extension School

Nicole Alexander

Professor at New York University

Hillary Green-Lerman

Senior Curriculum Lead at DataCamp

Sophie Searcy

Sr. Data Scientist at Metis

Bill Shander

Founder at Beehive Media

Thomas Fan

Software Developer - Machine Learning at Columbia Data Science Institute

Chris Van Pelt

Co-founder at Weights & Biases

Stacey Svetlichnaya

Deep Learning Engineer at Weights & Biases

CLICK HERE TO VIEW FULL SPEAKER LIST

Sessions on Data Science Kick-start Track

Workshop: Deciphering the Black Box: Latest Tools and Techniques for Interpretability
Talk: Adversarial Attacks on Deep Neural Networks
Training: Integrating Pandas with Scikit-Learn, an Exciting New Workflow
Workshop: Machine Learning for Digital Identity

Talk: Adding Context and Cognition to Modern NLP Techniques
Training: Good, Fast, Cheap: How to do Data Science with Missing Data
Workshop: Open Data Hub workshop on OpenShift
Talk: Practical AI Solutions within Healthcare and Biotechnology

Training: Apache Spark for Fast Data Science (and Fast Python Integration!) at Scale
Workshop: Reproducible Data Science Using Orbyter
Talk: Combining Millions of Products into One Marketplace Using Computer Vision and Natural Language Processing
See the whole schedule!

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, talks, and workshops on the most important tools and topics to help you quickly gain essential data science skills

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?

Accelerate and broaden your knowledge of key areas in data science, including deep learning, machine learning, and predictive analytics

With numerous introductory level workshops, you get hands-on experience to quickly build up your skills

Post-conference, get access to recorded talks online and learn from over 100+ high quality recording sessions that let you review content at your own pace

Take time out of your busy schedule to accelerate your knowledge of the latest advances in data science

Learn directly from world-class instructors who are the authors of and contributors to many of the tools and languages used in data science today

Meet companies ranging from hot startups to Fortune 500 looking to hire professionals with data science skills at all levels

Network at our numerous lunches and events to meet with data scientists, enthusiasts, and business professionals

Get access to other focus area content including, ML / DL, Data Visualization, Quant finance, and Open Data Science

Who Should Attend

The Data Science Kick-start track is ideal for anyone looking to learn the languages, tools, and topics of data science. Not only will you train in key areas of data science like deep learning and machine learning; you will also learn the tools and languages to implement modules such as TensorFlow, scikit-learn, Python, and R

Beginners interested in getting started in data science
Individuals seeking to better understand focus areas of data science such as deep learning, machine learning, text analytics etc.
Software engineers and software architects looking to employ machine learning and data science in their programming
Data wranglers and database specialists looking to leverage their existing data assets with data science tools and models
Business professionals interested in data science and looking to gain a deeper understanding

Experienced data scientists looking to enhance their data science skills
Anyone interested in learning data science languages such as Python, R, and Julia
Technologists looking to use the latest data science tools such as Apache Spark and TensorFlow to implement machine learning and deep learning
Students and academics looking for more practical applied training in data science tools and techniques
Industry experts looking to assess the impact of data science on their industry