ML& analytics using Python or R programming

Hours

8 Days

Defining a Machine learning and analytics professional

Certified Machine Learning and analytics professional is an overall expert in statistical analysis right from the basic descriptive statistics to predictive analytics, including text analytics

His /her razor sharp data analytical skills will help the organization to take maximum advantage of the available data, to take decisions in positioning the organization at maximum advantage in aspects such as market share, market penetration, sales and marketing, defining product variety, delivery , and post sales service , financial analysis , HR analytics etc..

Objective of the program

Make a candidate an expert in statistical analysis ,covering all topics including basic statistics, descriptive statistics, inferential statistics, hypothesis testing, predictive modeling techniques.
Give basic and adequate knowledge in Python or R programming (as per your choice) to perform all statistical analysis covered in the course

Who should attend this program

Any professional with 2 years or more work experience and with basic understanding of operating a laptop

Any professional who is interested in moving to analytics field in their career

Pedagogy followed

Alternate days of theory and practical classes to ensure optimum topic coverage along with exposure to practical usage

What is expected of a Machine learning & analytics professional in a company

To work on important data analytics requirements of the company
Responsible for data preparation, data visualization (Graphical) , validating assumptions using hypothesis testing and prediction using various predictive analytics tools and techniques to achieve business results

Things you should do to be a certified Machine learning & analytics professional

Complete an 8 full day training with TrainFirm adding up to 64 hours
Complete the 4 live projects using real data
Appear for the exam on the 8^th day and pass in the exam

Course Contents

Introduction to Python or R
Python or R Fundamentals
Mastering statistics required for ML
Univariate analysis using Python or R
Data Visualization
Data Preparation
Hypothesis Testing
Correlation and Regression
Logistic regression
Decision tree
Random forest
Segmentation and clustering
Timeseries/ARIMA
Text Analytics
4 Industry projects