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.
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Can I just enroll in a single course?
Can I take the course for free?
It is assumed you have a solid understanding of the following topics prior to starting this course: Fundamental understanding of Linear Algebra; Understanding of sampling, probability theory, and probability distributions; Knowledge of descriptive and inferential statistical concepts; General understanding of machine learning techniques and best practices; Practiced understanding of Python and the packages commonly used in data science: NumPy, Pandas, matplotlib, scikit-learn; Familiarity with IBM Watson Studio; Familiarity with the design thinking process. If you are unsure, Course 1 includes a Readiness Exam you can take to see if you are prepared.
Do I need to take the courses in a specific order?
You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones.
Will I earn university credit for completing the Specialization?
Sorry, you will not.
By the end of this specialization you will be able to:
1. Build an end to end AI solution.
2. Leverage Design Thinking as a framework to work through the translation of business goals into AI technical implementations.
3. Bring together different capabilities such as Machine Learning, and specialized AI use cases.
4. Leverage Python as the tool of choice for building AI models, while integrating IBM technologies to facilitate enterprise tasks such as cross-collaboration for the creation of machine learning models, employing out-of-the-box trained models for natural language processing and visual recognition, and deploying models to production.
Who should take this specialization?
This specialization targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on building and deploying AI in large enterprises. If you are an aspiring Data Scientist, this specialization is NOT for you as you need real world expertise to benefit from the content of these courses.
Can I take the certification exam here on Coursera?
How much does the certification exam cost?
I don't know anything about design thinking or Watson Studio. Can I still take this course?
It is highly recommended that you have at least a basic working knowledge of design thinking and Watson Studio prior to taking this course. Please visit the IBM Skills Gateway at http://ibm.com/training/badges and "Find a Badge" related to "design thinking" or "Watson Studio". From there you will be directed to courses covering these topics.
Do I have to use the IBM Cloud tools for this course?
No. Most of the exercises may be completed with open source tools running on your personal computer. However, the exercises are designed with an enterprise focus and are intended to be run in an enterprise environment that allows for easier sharing and collaboration. Some of the exercises in this specialization are heavily focused on deployment and testing of machine learning models and use the IBM Watson tooling found on the IBM Cloud.
Can I use my favorite open source tools for this course?
Yes. All IBM Cloud Data and AI services are based upon open source technologies.
What is the cost for using the IBM Cloud tools for this course?
The exercises in the course may be completed by anyone using the IBM Cloud "Lite" plan, which is free for use.
What tools are required to complete the courses in this specialization?
1. Python version 3, including libraries for data analytics, visualization and machine learning.
2. The Jupyter notebook libraries for Python version 3.
3. Access to the IBM Cloud at https://cloud.ibm.com and the Watson services on the IBM Cloud.