This exclusive bootcamp is an opportunity for Pharma and Healthcare professionals to learn and apply the very latest cutting edge technology in Big Data, Machine Learning and Advanced Analytics Technologies.
The course provides a practical foundation of the current state of Data Science and how to apply it across various sectors of healthcare to deliver advanced data mining, predictive and prescriptive analytics in large Pharmaceutical and Healthcare companies. The knowledge, skills and techniques you learn in this course will enable you to leapfrog your peers and competitors in leveraging big data for competitive advantage.
You pose the challenges, you pose the questions, we provide the answers – neutral, agnostic, independent and non-vendor specific.
The course is split into 2 days of working sessions - Day 1 involves a hands on introduction to the tools used in Data Science and Day 2 involves an interactive discussion and exploration of various real-world use cases of machine learning concepts being used in the health care sector.
- Big Data concepts
- Big Data tools
- Machine Learning concepts
- Machine Learning tools
- Data Mining using R and other tools
- Machine Learning using R and other tools
- R as a substitute for Excel
- Other Big Data Tools: Hadoop & Spark
- BI Tools for data science
- Improving daily workflow using R & other tools
- Big Data applications in Pharma & Healthcare
- Machine Learning in Pharma & Healthcare
- Real-World Data Science Use Cases in Pharma
- How to supercharge your pharma analytics using Data Science
- Pharma Industry & Management Perspective on Data Science
- Exploration of unmet needs in Pharma and how to use Data Science to solve them
- Interactive audience discussion
Who is interested?
- Mid-Senior Level Management of Departments currently using or considering Big Data
- Business Intelligence, Data Analytics and Big Data Professionals
- Professionals who are looking to leverage their skills in the Big Data world
What do I need?
- A laptop where you can plug in an USB drive! (Seriously, that is all you will need).
- A basic knowledge of statistics would be helpful, but not necessary
Meet the Instructor: Nataraj Dasgupta
Nataraj is the Vice President of Advanced Analytics at RxDataScience Inc. . Prior to his current role, he led the Data Science division at Purdue Pharma, L.P. and was responsible for the design, development and architecture of Purdue’s award-winning Big Data and Machine Learning Platform.
Nataraj has been in the IT industry for more than 19 years and has worked in the technology divisions of Philip Morris, IBM, UBS Investment Bank and Purdue Pharma. At UBS, Nataraj held the role of Associate Director working with High Frequency & Algorithmic Trading technologies used by investment banks and hedge funds on Wall St and other financial centers across the world. The finance industry has been implementing “Big Data” systems for many decades and has had a mature set of tools that has permitted traders and quants to analyse large volumes of trading-related data in the order of milliseconds. Despite Pharma's ubiquitous reliance on more traditional enterprise systems, Nataraj and the Systems Development & Analytics group led by Sayee Natarajan, chose to instead leverage technologies that were exclusively used in the financial domain and never before in a healthcare setting to analyse terabyte-scale medical and pharmaceutical datasets.
The effort led to a radically simple platform built using trading specific tools which were less expensive than conventional “Big Data” platforms, yet orders of magnitude faster in data processing capabilities facilitating tasks to complete in seconds compared to days in the existing and more popular Pharma enterprise systems. The platform received a wide recognition as one of the most advanced big data solutions for healthcare and led to several awards, including the recognition of Purdue Pharma as one of the top 25 most innovative technological divisions in the US by Information Week. In 2016, investors from Wall Street and the City of London provided funding for a new startup, RxDataScience Inc. responsible of commercialising the technology to the broader healthcare sector.