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)
Bethany Poulin is a data scientist and educator with expertise in statistical analysis, data visualization, and complex algorithmic problem-solving. She has worked as a professional data scientist and educator for the last 4 years and loves sharing what she has learned with her students. Her unusual background in Fine Arts and experience teaching high school give her a unique perspective on both problem-solving and the learning-teaching process. Prior to teaching this part-time course, she was a lead instructor in our Data Science Immersive program on the Boston campus. She teaches simply because she loves students and enjoys being a part of their success. She holds a BFA in Professional Photography from Rochester Institute of Technology, did post bachelor’s studies and the University of Montana in Environmental Biology, where she was recognized nationally as a Morris K Udall Scholar, is one semester away from an MS in Data Science from the City University of New York. She is has presented at PyOhio 2018 and 2019 and gave a presentation at ODSC East in 2019. In her spare time, Bethany is an avid fly fisherman, potter, and maker.
Introduction to Shiny Application Development(Half-Day Training)
Adewale (Wale) Akinfaderin is a Data Scientist at Amazon Web Services. His expertise is in machine learning, deep learning, statistical experimentation and general information theory. He has broad experience implementing and extending ML techniques to solve practical and business problems. In his spare time, he conducts research on Machine Learning for the Developing World.
Mathematics for Data Science and Machine Learning(Half-Day Training)
Changa has 20 years of Consulting experience implementing data and analytics solutions for cross sector clients with focus on reducing costs, improving operational efficiencies and adoption across different business functions. He has seen the transition from database solutions, packaged analytics to self-service advanced analytics over the last 2 decades.
Thomas J. Fan is a Staff Associate at the Data Science Institute at Columbia University. He is one of the core developers of scikit-learn, an open source machine learning library written in Python. Thomas holds a Masters in Mathematics from NYU and Masters in Physics from Stony Brook University. He also maintains skorch, a scikit-learn compatible neural network library that wraps PyTorch. He believes that developing open source software is one of the best ways to maximize one’s impact.
Introduction to Scikit-learn: Machine Learning in Python(Half-Day Training)
Ian Johnson is a User Experience Engineer at Google. He also organizes of Bay Area d3, starts with SVG and then dives deep into d3 including DOM manipulation, categorical and quantitative scales, axis, brushes, color schemes, events and histograms. Ian likes to make sense of data by exploring it visually with D3.js!
Painting with Data: Introduction to d3.js(Half-Day Training)
Training: Mathematics for Data Science and Machine Learning
Training: Getting Started with Pandas for Data Analysis
Training: Introduction to Machine Learning
Training: Hands-On Introduction to LSTMs in Keras/TensorFlow
Training: Introduction to Deep Learning for Engineers
Training: Introduction to Scikit-learn: Machine learning in Python
Bootcamp: Python Fundamentals
Bootcamp: Python for Data Acquisition
Talk: ML Easel – Tredence’s Data Science and ML Engineering Workbench
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
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