Machine learning combines data with statistical tools to predict an output. This output is then used by corporate to makes actionable insights. Machine learning is closely related to data mining and Bayesian predictive modeling. The machine receives data as input, use an algorithm to formulate answers.
you will learn about applications of Machine Learning in different fields such as health care, banking, telecommunication, and so on. You’ll get a general overview of Machine Learning topics such as supervised vs unsupervised learning, and the usage of each algorithm. Also, you understand the advantage of using Python libraries for implementing Machine Learning models.
Machine Learning Course Objectives
You will get an overview of how humongous amounts of data is being generated, how to draw meaningful business insights, techniques used to analyze structured and unstructured data, latest machine learning algorithms used to build advanced prediction models and how to visualize data. All these are learned from the perspective of solving complex business problems and making organizations profitable. Practical case studies which are industry relevant have been making our students stand out from the rest and achieve outstanding accolades from the best companies of the globe. Our students have been leaving new footprints in the corporate world by becoming industry-ready as soon as they graduate from colleges.
Machine Learning Training Requirements
Computer skills, basic Mathematics knowledge and knowledge of basic Data Science concepts.
Who Should Attend Machine Learning Course?
- 💠Candidates aspiring to be a Data Scientist, Big Data Analysists, Analytics Manager/Professionals, Business Analyst, Developer
- 💠Graduates who are looking to build a career in Data Science and Machine Learning
- 💠Employees – Organization is planning to shift to Big data tools
- 💠Mid-level Executives
- 💠Managers with knowledge of basic programming