Professional Certificate in IBM Data Science

edX

Course Features

Duration

12 months

Delivery Method

Online

Available on

Limited Access

Accessibility

Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Effort

6 hours per week

Teaching Type

Self Paced

Course Description

The demand for data science and machine learning skills is high across all industries. This means that the market for data professionals is growing. After completing the Professional Certificate program, your skills and experience will allow you to launch a career in machine learning and data science. You will learn real data science tools, real-world problems, and data sets through hands-on assignments. This curriculum will cover many data science topics, including open source tools and libraries and methodologies, Python, databases and SQL, data visualization, machine learning, machine learning, and data analysis. This program does not require any prior programming or computer science knowledge.

Anyone can learn to use computers and have a passion for learning. We start small and work our way up to more difficult problems.

This program is designed to help you jumpstart your career in data science. It also provides you with a portfolio data science deliverables that will give you the confidence you need to start your data scientist career.

Course Overview

International Faculty

Post Course Interactions

Instructor-Moderated Discussions

Case Studies, Captstone Projects

Skills You Will Gain

What You Will Learn

Apply various Data Science and Machine Learning skills, techniques, and tools to complete a project and publish a report

Practice with various tools used by Data Scientists and become experienced in using some of them like Jupyter notebooks

Master the key steps involved in tackling a data science problem and learn to follow a methodology to think and work like a Data Scientist

Write SQL to query databases and explore relational database concepts

Understand Python and practice Python programming using Jupyter

Import and clean data sets, analyze data, build and evaluate data models and pipelines using Python

Utilize several data visualization tools, techniques and libraries in Python to present data visually

Understand and apply various supervised and unsupervised Machine Learning models and algorithms to address real world challenges using Python

Course Content

Expand all sections

Module 1: Introduction to Data Science

Module 2: Data Science Tools

Module 3: The Data Science Method

Module 4: SQL for Data Science

Course Instructors

Romeo Kienzler

Chief Data Scientist

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 Eninee...

Saeed Aghabozorgi

PhD, Sr. Data Scientist

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 knowle...

Rav Ahuja

AI and Data Science Program Director

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...

Joseph Santarcangelo

PhD., Data Scientist

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.