Course Overview:
Become a Machine Learning (ML) specialist with the Machine Learning using Python and R program. Gain knowledge of ML algorithms and applications using the two most popular programming languages. Use Python and R to enable regression analysis and to build predictive models. Orient yourselves with Black Box techniques like Neural Networks and Support Vector Machine. Machine Learning Training using Python and R programming includes an overview of analytical techniques used to manipulate massive amounts of data and then driving meaningful business insights from the same. The course module demonstrates the various techniques used to analyze structured and unstructured data, build advanced prediction models with Machine Learning algorithms and Data Visualization. The course is loaded with practical case studies that enable the participants to solve complex business problems and improve profitability in their companies.
Course Objectives:
- Become familiar with analyzing data, computing statistical measures along with Data Wrangling, Data Cleansing, Data Manipulation, etc.
- Become familiar with Machine Learning algorithms including Black Box techniques such as Neural Networks and Support Vector Machine
- Become familiar with Regression algorithms and the application of Python, R as statistical software in Machine Learning and Data Science
- Build predictive models using Amazon Machine Learning Services
- Be able to create Data Visualization, Data Manipulation in different forms and draw meaningful business insights from the underlying data
Pre-requisites:
- Basic Mathematical Knowledge
- Basic Data Science Concepts
Target Audience:
- Candidates aspiring to be Data Scientist, Machine Learning Expert, Data Analyst, etc.
- Employees of organizations
- Managers with knowledge of basic programming and decision-makers
- Graduates
- Mid-level and Senior-level Executives
- Data Science and Data Analytics Professionals
Course Duration:
- 5 Days (35 Hours)
Course Content:
- Python, R Introduction and Installation
- Connecting A Variety of Data Sources using Python and R
- Machine Learning Primer using Python and R
- Handling Balanced versus Imbalanced Datasets
- Basic Statistics and Data Visualization using Python and R
- Data Manipulation using Python and R
- Functions and Programming in Python and R
- Data Mining Supervised, Unsupervised, Reinforcement Learning
- Linear and Logistic Regression using Python and R
- Decision Trees using Python and R
- Closing and Remarks
