Juan Kanggrawan is the current Head of Data Analytics at Jakarta Smart City. His key role is to fully utilize data to formulate public policy and to improve the quality of public services. Juan is currently working on several city-scale strategic analytics initiatives. He is actively analyzing complex, diverse and exciting urban data on a daily basis: citizen complaint/aspiration, transportation/mobility, health (COVID-19), CCTV, Open Data, weather-flood-river bank, subsidy utilization, food commodities price elasticity, etc. He is also developing and aligning a strategic partnership framework between Jakarta Smart City with other government agencies, business enterprises, research agencies, and universities.
Soham Chakraborty is a Senior Data Scientist with a Statistical background. He works mostly in Manufacturing creating AI solutions using Machine Learning and Deep Learning techniques.
Upasana Roy Chowdhury is a data science consultant with supply chain and manufacturing experience.
Venkata Pingali is an academic-turned entrepreneur. He works at the intersection of data, ML algorithms, and systems. He builds data products to speed up the adoption of ML in the enterprise. Scribble Data, his firm, offers a platform and managed service to production feature engineering.
Oliver Gindele is head of machine learning at Datatonic. Oliver is passionate about using computer models to solve real-world problems. Working with clients in retail, finance, and telecommunications, he applies deep learning techniques to tackle some of the most challenging use cases in these industries. He studied materials science at ETH Zurich and holds a PhD in computational physics from UCL.
Tomek is a Software engineer at Polidea, Apache Airflow committer and book lover. He fancies functional programming because he is graduated mathematician. Every day he tries to make the world a better place.
Tom is a Junior Principal Data Engineer at QuantumBlack, a McKinsey Company. Prior to consulting, Tom was CTO and co-founder of Commandiv, a wealth management startup.
Francesca Lazzeri, PhD is a machine learning scientist, author, and speaker. She leads an international team of data scientists, developers and cloud advocates at Microsoft. Before joining Microsoft, she was a research fellow at Harvard University in the Technology and Operations Management Unit.
She is also a board member of Microsoft “Women@NERD” association, data science mentor at the Massachusetts Institute of Technology and Columbia University, and active member of the AI community.
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 post conference
Take time out of your busy schedule to accelerate your knowledge on the latest advances in data science practice and management
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 hiring 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 machine learning & deep learning, data visualization, and much more
Data scientists moving beyond model experimentation looking to understand production workflow
Data scientists seeking to improve the overall practice of management and development
Anyone interested in understanding better collaborative and agile management techniques as applied to data science
Business professionals and industry experts looking to understand data science in practice
Software engineers and technologists who need to work with data science workflows and understand the unique requirements of these systems
CTO, CDS, and other managerial roles that require a bigger picture view of data science
Technologists in the field of DevOps, databases, project management and others looking to break into data science
Students and academics looking for more practical applied training in data science tools and techniques