Overview
Machine Learning is one of the most in-demand skills for jobs related to modern AI applications, a field in which hiring has grown 74% annually for the last four years (LinkedIn). It also complements your learning with special topics, including Time Series Analysis and Survival Analysis.
This IBM Machine Learning course offered by Coursera in partnership with IBM consists of 6 courses providing you with solid theoretical understanding and considerable practice of the main algorithms, uses, and best practices related to Machine Learning . You will follow along and code your own projects using some of the most relevant open source frameworks and libraries.
Although it is recommended that you have some background in Python programming, statistics, and linear algebra, this intermediate series is suitable for anyone who has some computer skills, interest in leveraging data, and a passion for self-learning. We start small, provide a solid theoretical background and code-along labs and demos, and build up to more complex topics.
In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Machine Learning.
Applied Learning Project
This Professional Certificate has a strong emphasis on developing the skills that help you advance a career in Machine Learning. All the courses include a series of hands-on labs and final projects that help you focus on a specific project that interests you. Throughout this Professional Certificate, you will gain exposure to a series of tools, libraries, cloud services, datasets, algorithms, assignments and projects that will provide you with practical skills with applicability to Machine Learning jobs. These skills include:
- Tools: Jupyter Notebooks and Watson Studio
- Libraries: Pandas, NumPy, Matplotlib, Seaborn, ipython-sql, Scikit-learn, ScipPy, Keras, and TensorFlow.
Get more details
Visit programme websiteProgramme Structure
Courses included:
Exploratory Data Analysis for Machine Learning
Supervised Learning: Regression
Supervised Learning: Classification
Unsupervised Learning
Deep Learning and Reinforcement Learning
Specialized Models: Time Series and Survival Analysis
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 3 months
- 10 hrs/week
Start dates & application deadlines
Language
Delivered
- Self-paced
Disciplines
Computer Sciences Web Technologies & Cloud Computing Machine Learning View 265 other Short Courses in Machine Learning in United StatesExplore more key information
Visit programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Intermediate Level
- Python programming, statistics, linear algebra
Make sure you meet all requirements
Visit programme websiteTuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 3 months. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 3 months.
You can choose from hundreds of free courses, or get a degree or certificate at a breakthrough price. You can now select Coursera Plus, an annual subscription that provides unlimited access.
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.