Machine Learning for Data Science using R
Popular Career ChoiceMajor investment by companies like IBM and HP in big data has made it a popular career option.
Job OpportunitiesAfter the machine learning online course, you’ll be eligible to apply for the 1.9 million available jobs.
Who Should AttendEngineers, managers, analysts, business intelligence professionals
Salary PackagesThe average pay for a Data Scientist with Machine Learning skills is ₹8.7 lakhs per year.
Expert FacultyLearn from experts with a vast experience in delivering Machine Learning lectures and training.
Are you looking to build a career in the exciting field of data analysis and Machine Learning? Machine Learning is the science of using computers to run predictive models that learn from existing data in order to forecast future behaviours, outcomes, and trends. It is an in-demand skill for all major organizations and a must-have for all aspiring data scientists and engineers.
Manipal ProLearn’s course in Machine Learning for Data Science using R will provide you with a broad understanding of Machine Learning. The course will help you to gain experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval.
After completing the Machine Learning training course, you’ll be considered as a strong and competent data scientist. The course will help you to:
- Identify the right machine learning approach (supervised/unsupervised).
- Identify whether it’s a classification or regression based problem
- Get the relevant algorithm and build a machine learning model
- Derive the accuracy of the machine learning model using Goodness Measures & ROC
- Use Clustering methods to model unstructured data
- Identify a domain (customer analytics) and apply the relevant concepts taught.
Engineers and non-engineers interested in Machine Learning
Managers and analysts interested in understanding technical aspects of Machine Learning
Business Intelligence professionals entering data analytics projects
Data Science aspirants
Introduction to Machine Learning
Broad classification – Supervised vs Unsupervised Learning
Use cases, Opportunities and Challenges
Machine Learning -definition, learning approaches supervised & unsupervised, use cases, challenges and opportunities.
KNN - ‘K’ Nearest Neighbors
Build Classification based machine learning models using algorithms Decision Trees & k-NN.
Derive the accuracy of the machine learning model using Goodness Measures & ROC
Practical Issues in Clustering
Develop models from unstructured data using clustering techniques and understand it’s limitation
Customer Life Cycle and Customer Behavior
Understand the concepts of customer lifecycle & behaviour which aids in building better customer analytics based ML models
Manipal ProLearn, a part of Manipal Global Education Services, offers a variety of professional certification courses across Technology, Digital Marketing, Data Sciences, Project Management, and Finance domains.
Carrying forward the Manipal legacy of over six decades in education, Manipal ProLearn helps working professionals and students to enhance their skills and fast-track their careers. Manipal ProLearn has partnered with industry leaders like Google, Microsoft, AWS Educate, EY, Sandbox, and Chartered Institute of Management Accountants (CIMA) to provide quality courses that add to your skill set.
We have redefined learning in the professional certification program space with a wide range of course options taught by expert faculty on an award-winning learning platform. Benchmarked against global certification standards of PMI, CIMA, PMBOK etc., our course content is designed and developed by industry experts. Not only are these certification courses good for skill enhancement, but with industry-recognised certification, they are also a great value-add to one's resume. Over the last two years, more than 80,000 learners have advanced their careers with the help of our courses
Currently, none of the courses has an entrance test. But some certifications might have their prerequisites, which are mentioned on the respective course pages.
Once you have enrolled in a course, you will receive a welcome e-mail and a telephonic call from our customer support team. The features offered as part of the course will be explained clearly by our representative and also will also be listed in the mail correspondence.
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The course material access will be active till the validity of your course which is 12 months from the date of your enrolment.
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