Predictive Analytics & Machine Learning Training

We introduce practical applications of Machine Learning in our Predictive Analytics & Machine Learning Training. Predictive Analtycs is at the cutting edge of decision making in many leading businesses and governments around the world.

Regression models are being used to predict consumer demand and Classification models are being used to predict if a loan-applicant should be granted a loan or not. A/B testing is being employed to determine which color in a marketing add generates more revenue and recommender systems are being used by E-commerce stores to determine which items a first-time visitor maybe interested in.

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Topics covered in Machine Learning Training Module

Introduction to Machine Learning
Linear Regression
Logistic Regression
Classification
Decision Tree & Random Forest
K- Means Clustering

Bayesian ML : A/B Testing
Support Vector Machines
Recommender Systems
Principal Component Analysis
Brief introduction to Natural Language Processing (NLP)
Brief introduction to Neural Networks & Deep Learning

Once you have mastered topics covered in our Machine Learning Training Module, you can apply your skills in any department in any industry. May it be in HR for a Logistics Company, Sales of a Retail Giant or even Engineering Analysis in a Utility Company. Machine Learning is going to be everywhere very soon!

Prerequisite for this Course

Participants in this course must have completed our course on Big Data Analytics.
Or they must demonstrate good understanding of the following topics by passing an examination prior to course registration.
- Fundamentals of Statistics. This course will be heavily using Statistical concepts to build AI models and it is expected participants have a robust understanding of Statistics.
- Data Exploration & Statistical Modeling. This course build on our previous course of Big Data Analytics. It is expected that participants of this course have a good understanding of how to conduct Data Exploration & set-up Statistical Models.
- We offer Discount Packages for the prerequisite introductory courses needed to successfully complete this course. Contact our team to know more.
Big Data Analytics is an evolving science with new and unique applications cropping up every day. Check out our carefully planned and recommended sequence of training courses that will ensure you gain all the necessary skills needed in a systematic and meaningful way to succeed as a Data Scientist!

Our carefully planned and recommended learning structure for Data Science Series

Level	Course Name	Know More
Basic I	Fundamentals of Statistics	Click here
Basic II	Data interpretation with BI Dashboards	Click here
Intermediate I	Learning R for Data Visualization and Analytics	Click here
Intermediate II	Big Data Analytics with R	Click here
Advanced I	Predictive Modeling & Machine Learning	Click here
Advanced II	Artificial Intelligence with Python	Click here
Advanced III	Using Big Data Analytics in Business	Click here

Machine Learning Training Course Schedule

Course	Location	Course Format	Start Date	End Date	Duration	Register
Machine Learning & Predictive Analytics	Dubai	Weekend Batch	6th October 2018	15th November 2018	6 Weeks	Register Here

Predictive Analytics & Machine Learning Training Course Details

- Duration of the course is 32 hours.
- This course is offered as ,
  - 4 Day Intensive Boot-Camp.
  - Evening Classes. Two 2-hour sessions a week for eight weeks in the evenings.
  - As part of our Six Month Associate in Big Data Analytics.
  - We are currently offering the course in Dubai, Abu Dhabi, Singapore, Delhi, Mumbai & Bangalore.
  - Checkout the course schedule for more information.

Participants must bring their own laptop. Preferably with more than 8GB ram.
Our Machine Learning Training Module will be mainly taught using Python as the programming language. While we will cover necessary topics in Python as needed for this course, participants interested to further explore programming in Python can check out Programming in Python.
All softwares and Databases used for the course are open-source and participants will be taught how to install and set-up the environment.
All training topics covered in the course will be taught using relevant industry specific case studies and examples.
The course is very hands-on/practical and is not a lecture or seminar. Participants will be expected to complete exercises and case studies on their own with necessary support and guidance from the instructor.