San Francisco | Oct 29th – Nov 1st, 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 3 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, topic, and techniques in use to ensure you hit the ground running.

Some of Our Current Speakers

Jared Lander

Chief Data Scientist, Author of R for Everyone, Professor at Lander Analytics, Columbia Business School

Andreas Mueller, PhD

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

Dr. Kirk Borne

Principal Data Scientist at Booz Allen Hamilton

Bin Fan, PhD

Founding Engineer & VP Open Source at Alluxio

Scott Cronin, PhD

Senior Data Scientist at ShopRunner

Jane Adams

Data Visualization Artist at University of Vermont Complex Systems Center

Lars Hulstaert

Data Scientist at Microsoft

Samuel Taylor

Data Scientist at Indeed

Jacob Schreiber

PhD Candidate at University of Washington

See the full list here!

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 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

Python 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 and contributors to many of the tools and languages used in data science today

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

Network at our numerous lunches and events to meet 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. You will train in key areas of data science like deep learning and machine learning, and 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