This Artificial Intelligence Training will first take you through Introduction to Data Science and Statistical Analytics, Introduction to R Programming, Data Exploration, Data Wrangling and R Data Structure. It will teach you Data Visualization like Bar Graph, Histogram, Correlogram etc.
This AI Training will also explain Predictive Modeling (Linear Regression, Logistic Regression) using AI. It will also explian you concepts like Decision Tree, Random Forest etc. This AI Training will introduce you to Neural Networks and Time Series.
The main highlight of this AI training will be the projects and case studies. In this course you will able to do different projects and case studies which will clear all the concepts you will learn during this Artificial Intelligence Training.
Few of the clients we have served across industries are:
DHL | PWC | ATOS | TCS | KPMG | Momentive | Tech Mahindra | Kellogg's | Bestseller | ESSAR | Ashok Leyland | NTT Data | HP | SABIC | Lamprell | TSPL | Neovia | NISUM and many more.
MaxMunus has successfully conducted 1000+ corporate training in India, Qatar, Saudi Arabia, Oman, Bangladesh, Bahrain, UAE, Egypt, Jordan, Kuwait, Srilanka, Thailand, HongKong, Germany, France, Australia and USA.
AI Course Duration: 35-40 Hours
AI Training Timings: Week days 1-2 Hours per day (or) Weekends: 2-3 Hours per day
AI Training Method: Online/Classroom Training
AI Study Material: Soft Copy
Introduction to Data Science and Statistical Analytics
Introduction to R
Data Exploration, Data Wrangling and R Data Structure
Introduction to Statistics
Predictive Modeling – 1 ( Linear Regression) Using AI
Predictive Modeling – 2 (Logistic Regression) Using AI
Association Analysis and Recommendation engine
Introduction to Neural Networks
Data Science Projects
Project 1 : Augmenting retail sales with Data Science
Industry : Retail
Problem Statement : How to deploy the various rules and algorithms of Data Science for analyzing stationary store purchase data.
Topics : In this project you will deploy the various tools of Data Science like association rule, Apriori algorithm in R, support, lift and confidence of association rule. You will analyze the purchase data of the stationary outlet for three days and understand the customer buying patterns across products.
Project 2 : Analyzing pre-paid model of stock broking
Industry : Finance
Problem Statement : Finding out the deciding factor for people to opt for the pre-paid model of stock broking.
Topics : In this Data Science project you will learn about the various variables that are highly correlated in pre-paid brokerage model, analysis of various market opportunities, developing targeted promotion plans for various products sold under various categories. You will also do competitor analysis, the advantages and disadvantages of pre-paid model.
Project 3 : Cold Start Problem in Data Science
Industry : Ecommerce
Problem Statement : how to build a recommender system without the historical data available
Topics : This project involves understanding of the cold start problem associated with the recommender systems. You will gain hands-on experience in information filtering, working on systems with zero historical data to refer to, as in the case of launching a new product. You will gain proficiency in working with personalized applications like movies, books, songs, news and such other recommendations. This project includes the various ways of working with algorithms and deploying other data science techniques.
Project 4 : Recommendation for Movie, Summary
Topics : This is real world project that gives you hands-on experience in working with a movie recommender system. Depending on what movies are liked by a particular user, you will be in a position to provide data-driven recommendations. This project involves understanding recommender systems, information filtering, predicting ‘rating’, learning about user ‘preference’ and so on. You will exclusively work on data related to user details, movie details and others. The main components of the project include the following:
The Market Basket Analysis (MBA) case study
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