Advanced Data Science with IBM Specialization

Starts Oct 23

Advanced Data Science with IBM Specialization

Expert in Data Science, Machine Learning and AI. Become an IBM-approved Expert in Data Science, Machine Learning and Artificial Intelligence.

About This Specialization

As a coursera certified specialization completer you will have a proven deep understanding on massive parallel data processing, data exploration and visualization, and advanced machine learning & deep learning. You'll understand the mathematical foundations behind all machine learning & deep learning algorithms. You can apply knowledge in practical use cases, justify architectural decisions, understand the characteristics of different algorithms, frameworks & technologies & how they impact model performance & scalability. If you choose to take this specialization and earn the Coursera specialization certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging.

Created by:

courses
4 courses

Follow the suggested order or choose your own.

projects
Projects

Designed to help you practice and apply the skills you learn.

certificates
Certificates

Highlight your new skills on your resume or LinkedIn.

Projects Overview

Courses
Advanced Specialization.
Designed for those already in the industry.
  1. COURSE 1

    Fundamentals of Scalable Data Science

    Subtitles
    English, Vietnamese

    About the Course

    The value of IoT can be found within the analysis of data gathered from the system under observation, where insights gained can have direct impact on business and operational transformation. Through analysis data correlation, patterns, trends, and other
  2. COURSE 2

    Advanced Machine Learning and Signal Processing

    Subtitles
    English

    About the Course

    >>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< This course, Advanced Machine Learning and Signal Processing, is part of the IBM
  3. COURSE 3

    Applied AI with DeepLearning

    Commitment
    4 weeks of study, 4-6 hours/week
    Subtitles
    English

    About the Course

    >>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< This course, Applied Artificial Intelligence with DeepLearning, is part of the IBM
  4. COURSE 4

    Advanced Data Science Capstone

    Subtitles
    English

    About the Course

    This project completer has proven a deep understanding on massive parallel data processing, data exploration and visualization, advanced machine learning and deep learning and how to apply his knowledge in a real-world practical use case

Creators

  • IBM

    IBM is recognized as one of the leading experts in machine learning and artificial intelligence.

    IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.

  • Tom Hanlon

    Tom Hanlon

    Training Director
  • Ilja Rasin

    Ilja Rasin

    Data Scientist
  • Romeo Kienzler

    Romeo Kienzler

    Chief Data Scientist, Course Lead
  • Max Pumperla

    Max Pumperla

    Deep Learning Engineer
  • Niketan Pansare

    Niketan Pansare

    Senior Software Engineer
  • Nikolay Manchev

    Nikolay Manchev

    Data Scientist

FAQs