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Training Description:

Data science is making us smarter and more innovative in so many ways. How does it all work? In this Data Science and Analytics Professional Certificate program you will gain insight into the latest data science tools and their application in finance, health care, product development, sales and more. With real world examples, we will demonstrate how data science can improve corporate decision-making and performance, personalize medicine and advance your career goals.

Taught by a distinguished team of professors at Columbia University’s Data Science Institute, this program is perfect for anyone who wants to understand basic concepts in data science without getting into the weeds of programming. Aimed at organization leaders, business managers, health care professionals and anyone considering a career in data science, this program will steep learners in the fundamentals of statistics, machine learning and algorithms. It will also introduce emerging technologies such as the Internet of Things (IoT) , or wirelessly connected products, and techniques that allow computers to summarize mountains of text, audio and video. Concrete examples provided throughout the program will ensure that learners fully grasp and master key concepts.

Job Outlook

• The use of analytics has grown exponentially in all areas, including healthcare, government, retail, e-commerce, media, manufacturing, and the service industry
• Training in data science and analytics creates a pathway to jobs like Software Developer, Systems Engineer, Network Engineer, and Systems Administrator.

Real Career Impact

"At Microsoft, we see the need for skilled data professionals every day. The exponential growth in the volume of data being created is fundamentally changing our industry, and is creating amazing new career opportunities as companies consider how to unlock the insights from all of the data they’re collecting."

— Chris Roy , Senior Director of Learning Services, Microsoft Corporation

Additional information

What You'll Learn:

• The history of data science, tangible illustrations of how data science and analytics are used in decision making across multiple sectors today, and expert opinion on what the future might hold
• A practical understanding of the fundamental methods used by data scientists including; statistical thinking and conditional probability, machine learning and algorithms, and effective approaches for data visualization
• The major components of the Internet of Things (IoT) and the potential of IoT to totally transform the way in which we live and work in the not-to-distant future
• How data scientists are using natural language processing (NLP), audio and video processing to extract useful information from books, scientific articles, twitter feeds, voice recordings, YouTube videos and much more

Speakers:

Tian Zheng

Series CreatorColumbia University

Kathy McKeown

Henry and Gertrude Rothschild Professor of Computer ScienceColumbia University

Ansaf Salleb-Aouissi

Department of Computer ScienceColumbia University

Cliff Stein

Professor of IEOR and of Computer ScienceColumbia University

David Blei

Professor of Computer Science and StatisticsColumbia University

Itsik Peer

Associate Professor of Computer ScienceColumbia University

Mihalis Yannakakis

Professor of Computer ScienceColumbia University

Peter Orbanz

Assistant Professor of StatisticsColumbia University

Fred Jiang

Assistant Professor in the Electrical Engineering DepartmentColumbia University

Julia Hirschberg

Percy K. and Vida LW Hudson Professor of Computer ScienceColumbia University

Michael Collins

Vikram S. Pandit Professor of Computer ScienceColumbia University

Shih-Fu Chang

Richard Dicker Chair ProfessorColumbia University

Zoran Kostic

Associate Professor of Professional Practice & Director of the MS EE ProgramColumbia University

Andrew Gelman

Professor of Statistics and Political ScienceColumbia University

David Madigan

Executive Vice President and Dean of Faculty of Arts and SciencesColumbia University

Lauren Hannah

Assistant Professor in the Department of StatisticsColumbia University

Eva Ascarza

Assistant Professor of Marketing at Columbia Business SchoolColumbia University

James Curley

Assistant Professor of PsychologyColumbia University