Some Of Our Instructors
Dipanjan (DJ) SarkarLead Data Scientist | Google Developer Expert - ML Constructor Learning, Zurich
Dipanjan (DJ) Sarkar
Dipanjan (DJ) Sarkar is an acknowledged Data Scientist, published Author and Consultant with over nine years of industry experience in all things data. He was recognized as a Google Developer Expert in Machine Learning by Google in 2019, and a Champion Innovator in Cloud AI\ML by Google in 2022. He currently works as a Lead Data Scientist at Constructor Learning (formerly Schaffhausen Institute of Technology (SIT) Learning), Zurich.
Dipanjan has led advanced analytics initiatives working with Fortune 500 companies like Intel, Applied Materials, Red Hat / IBM. He works on leveraging data science, machine learning and deep learning to build large- scale intelligent systems. Dipanjan also works as an independent consultant, mentor and AI advisor in his spare time collaborating with multiple universities, organizations and startups across the globe. His passion includes solving challenging data problems as well as educating and helping people upskill in all things data. Find more about him at https://djsarkar.com
Bharti Motwani is the sole author of many books “Data Analytics with R” (Wiley), “Data Analytics using Python” (Wiley), “HR Analytics: Practical Approach using Python” (Wiley), “Machine Learning for Text and Image data: Practical Approach with Business Use Cases”
(Wiley) etc. Ambitious and analytical professional; IT and analytics consultant and corporate trainer; Result driven and articulate academician who can think “out of the box”, with more than 25 years of experience in teaching at professional and premium institutes at global level, research and software development. Demonstrated proficiency in writing books, editing and reviewing journals, and writing more than 50 research papers in leading international and national journals.
Big Data Analysis with PySpark (Workshop)
Hugo Bowne-Anderson, PhD
Hugo Bowne-Anderson is a data scientist, writer, educator & podcaster. His interests include promoting data & AI literacy/fluency, helping to spread data skills through organizations and society and doing amateur stand up comedy in NYC. He does many of these at DataCamp, a data science training company educating over 3 million learners worldwide through interactive courses on the use of Python, R, SQL, Git, Bash and Spreadsheets in a data science context. He has spearheaded the development of over 25 courses in DataCamp’s Python curriculum, impacting over 170,000 learners worldwide through my own courses. He hosts and produce the data science podcast DataFramed, in which he uses long-format interviews with working data scientists to delve into what actually happens in the space and what impact it can and does have. He earned PhD in Mathematics from the University of New South Wales, Australia and has conducted biomedical research at the Max Planck Institute in Germany and Yale University, New Haven.
Vaishali is a lead data scientist at Indium Software, a leading digital engineering company. She has 9 years of experience in the advanced analytics domain. She manages a large data science team, does project planning and builds enterprise grade analytics models for various real-world usecases. As a technology evangelist, Vaishali also coaches aspiring professionals on data science, machine learning and various advanced analytics technologies like natural language processing, computer vision, deep learning etc., She holds a professional postgraduate in Artificial Intelligence & Machine Learning.
Transformers for Document Understanding(Tutorial)
Sheamus McGovern is the founder of ODSC (The Open Data Science Conference). He is also a software architect, data engineer, and AI expert. He started his career in finance by building stock and bond trading systems and risk assessment platforms and has worked for numerous financial institutions and quant hedge funds. Over the last decade, Sheamus has consulted with dozens of companies and startups to build leading-edge data-driven applications in finance, healthcare, eCommerce, and venture capital. He holds degrees from Northeastern University, Boston University, Harvard University, and a CQF in Quantitative Finance.
Chaine San Buenaventura
Chaine San Buenaventura is the co-founder of Voilabs, an early-stage AI startup based in Paris specializing in voice chatbots for customer service. They are exploring the transformative capabilities of AI in reshaping digital interactions and are committed to driving innovation in this space. Chaine continues to contribute her expertise to Wizy.io, where she has been serving as the Lead Machine Learning Engineer, assisting in the advancement of their AI initiatives. Passionate about the future of AI, Chaine consistently explores the intersection of deep learning and natural, context-rich digital interactions, continually pushing the boundaries of what’s possible in Human-Machine Interaction. Her years of dedicated work in developing AI solutions and active participation in research, conferences, and community dialogues underscore her commitment to AI innovation and knowledge-sharing in the expanding field.
Jayeeta is a Senior Data Scientist with several years of industry experience in Natural Language Processing (NLP), Statistical Modeling, Product Analytics and implementing ML solutions for specialized use cases in B2C as well as B2B domains. Currently, Jayeeta works at Fitch Ratings, a global leader in financial information services. She is an avid LP researcher and gets to explore a lot of state-of-the-art open-source models to build impactful products and firmly believes that data, of all forms, is the best storyteller. Jayeeta also led multiple NLP workshops in association with Women Who Code, and GitNation among others. Jayeeta has also been invited to speak at International Conference on Machine Learning (IML 2022), ODSC East, MLConf EU, WomenTech Global Conference, Data Science Salon, The Al Summit, and Data Summit Connect, to name a few. Jayeeta is also an ambassador for Women in Data Science, at Stanford University, and a Data Science Mentor at Girl Up, United Nations Foundation, and WomenTech Network where she aims to inspire more women to take up STEM. Jayeeta has been nominated for the WomenTech Global Awards 2020 and has been spotlighted in the List of Top 100 Women Who Break the Bias 2022. More information here – https://linktr.ee/JayeetaP
A M Aditya
Aditya is a tech enthusiast with more than 7 years of experience across various technologies in data science, machine learning, deep learning and computer vision. He has completed his Masters in Data Science from the National University of Singapore. He has worked across various domains including automotive, banking, retail among others consulting various clients around the globe. He is a true believer of ‘You got to see it work to know it works’ and sets goals towards achieving the same in any of the endeavours he undertakes. Being highly inclined towards technology, he founded Xaltius Pte. Ltd in Singapore which has a major focus on building solutions in Data Science and AI and educating students and professionals in the same areas. He also founded Code for India which specializes in delivering top notch skills in Data Science and AI as required in the industry today. Apart from work, he loves to engage with kids and get involved in social work.
Xander Song is a Machine Learning Engineer and Developer Advocate at Arize AI and one of the creators of Phoenix, a popular notebook-first python library that leverages embeddings to uncover problematic cohorts of LLM, CV, NLP and tabular models. Before joining Arize, Song worked as a machine learning engineer at early stage AI startups. He is based in Oakland, California.
ODSC Workshop Includes
Opportunities to form working relationships with some of the world’s top data scientists for follow-up questions and advice.
Access to 70+ workshops.
Hands-on experience with the latest frameworks and breakthroughs in data science.
Affordable workshop–equivalent workshops at other conferences costs much more.
Professionally prepared learning materials, custom- tailored to each course.
Opportunities to connect with other ambitious, like-minded data scientists.