IBM Data Science

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Data science and machine learning skills continue to be in highest demand across industries, and the need for data practitioners is booming. Upon completing this Professional Certificate program, you will be armed with the skills and experience you need to start your career in data science and machine learning. Through hands-on assignments and high-quality instruction, you will build a portfolio using real data science tools and real-world problems and data sets. The curriculum will cover a wide range of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. There is no requirement for prior computer science or programming knowledge in order to take this program.

Anyone with some computer skills and a passion for self-learning can succeed as we begin small and build up to more complex problems and topics.

With the tremendous need for data science and data analyst professionals in the market today, this program will jumpstart your path in data science and prepare you with a portfolio of data science deliverables to give you the confidence to take the plunge and start your data science career.

المدربين

Alex Aklson
Alex Aklson
Alex Aklson, Ph.D., is a data scientist in the Digital Business Group at IBM Canada. Alex has been intensively involved in many exciting data science projects such as designing a smart system that could detect the onset of dementia in older adults using longitudinal trajectories of walking speed and home activity. Before joining IBM, Alex worked as a data scientist at Datascope Analytics, a data science consulting firm in Chicago, IL, where he designed solutions and products using a human-centred, data-driven approach. Alex received his Ph.D. in Biomedical Engineering from the University of Toronto.
Romeo Kienzler
Romeo Kienzler

Romeo Kienzler holds a M. Sc. (ETH) in Information Systems, Bioinformatics & Applied Statistics (Swiss Federal Institute of Technology). He has nearly two decades of experience in Software Enineering, Database Administration and Information Integration. Since 2012 he works as a Data Scientist for IBM. He published several works in the field with international publishers and on conferences. His current research focus is on massive parallel data processing architectures. Romeo also contributes to various open source projects.

Svetlana Levitan
Svetlana Levitan

Senior Developer Advocate with IBM Center for Open Data and AI Technologies, Svetlana has been a software engineer and technical lead for SPSS for many years. She works on open standards for machine learning model deployment PMML and ONNX. She holds PhD in Applied Math and MS in CS from University of Maryland, College Park. Svetlana loves to learn new technologies, share her expertise, and to encourage women in STEM.

Maureen McElaney
Maureen McElaney

Maureen McElaney is a Developer Advocate at IBM Center of Open Source Data and Ai Technologies. She is on the LF AI Trusted AI Committee underneath the Linux Foundation. She is an organizer for Women in Machine Learning and Data Science and on the board of the Vermont Technology Alliance. She is an experienced community builder and is passionate about building diversity (of all kinds) in tech through education, mentorship, and advocacy.

Rav Ahuja
Rav Ahuja

Rav Ahuja is a Global Program Director at IBM. He leads growth strategy, curriculum creation, and partner programs for the IBM Skills Network. Rav co-founded Cognitive Class, an IBM led initiative to democratize skills for in demand technologies. He is based out of the IBM Canada Lab in Toronto and specializes in instructional solutions for AI, Data Science, and Cloud. Rav presents at events worldwide and has authored numerous papers, articles, books and courses on subjects in managing and analyzing data. Rav holds B. Eng. from McGill University and MBA from University of Western Ontario.

Joseph Santarcangelo
Joseph Santarcangelo
Joseph Santarcangelo is currently working as a Data Scientist at IBM. Joseph has a Ph.D. in Electrical Engineering. His research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition.
Azim Hirjani
Azim Hirjani

Azim Hirjani is a Data Scientist Intern at IBM and is pursuing a BS in Computer Science from the University of Toronto. He creates content for various IBM Data Science courses on platforms such as Coursera and Edx. He has worked as a Data Wrangler at Equifax, utilizing Big Data technologies and has interests in Reinforcement Learning and Real Estate.

Saishruthi Swaminathan
Saishruthi Swaminathan

Saishruthi Swaminathan is a data scientist and developer advocate in the IBM CODAIT team whose main focus is to democratize data and AI through open source technologies. She has a Masters in Electrical Engineering specializing in Data Science and a Bachelor degree in Electronics and Instrumentation. Her passion is to dive deep into the ocean of data, extract insights, and use AI for social good. Previously, she was working as a Software Developer. On a mission to spread the knowledge and experience, she acquired in her learning process. She also leads the education for rural children initiative and organizing meetups focussing on women empowerment.

Saeed Aghabozorgi
Saeed Aghabozorgi
Saeed Aghabozorgi, PhD is a Sr. Data Scientist in IBM with a track record of developing enterprise level applications that substantially increases clients’ ability to turn data into actionable knowledge. He is a researcher in data mining field and expert in developing advanced analytic methods like machine learning and statistical modelling on large datasets.
Yan Luo
Yan Luo

Yan Luo, Ph.D., is a data scientist and developer at IBM Canada. Yan has been building innovative AI and cognitive applications in various areas such as mining software repositories, personalized health management, wireless networks, digital banking, etc. Yan received his Ph.D. in Machine Learning from the University of Western Ontario.