What is Data Visualization in Advanced Analytics
Data Visualization is the visual processing of information that has been unexplained in some schematic form. Data Visualization is a feature integrated in Business Analytics allowing executives to have precise understanding of the reports that are extracted out of millions of data by developing a visual context around it. Simply, Data Visualization interpret complicated data into accessible, intelligible, and usable form.
What is Artificial Intelligence
The wider concept of Machine Learning is Artificial Intelligence. It allows program to be work on its intelligence by gathering data by itself.
What is Big Data.
Big Data deals with database processing, predictive analysis and user behaviour of the user.
Big Data application has been widely in demand as large technologies and other industries are spending millions of amount to analyse and store large amount of data.
About Course
This course provides you a complete overview of Data Science, Machine Learning, Big Data, and Artificial Intelligence, teaching you complete applications of Machine Learning and Advanced Analytical Techniques.
With basic concepts and types of learning, it teaches you -
Supervised Learning: Building a model for predicting or estimating an output based on one or more inputs
Unsupervised Learning: Building a model with input data (but no outputs) to learn relationships and structure in the data
Reinforcement Learning: Reinforcement learning is learning what to do—how to map situations to actions
Supervised Learning and Techniques in Supervised Learning
Regression:Building a model when output is numerical e.g. Use of forecasting to support multiple functions
Classification:Building a model when output is categorical e.g. Personalized Offers and Promotions
Lab Work for Regression and Classification
Unsupervised Learning and Techniques in Unsupervised Learning
Clustering: A set of techniques for finding subgroups, or clusters, in a dataset e.g. Customer Segmentation, Fraud Detection
Dimensionality Reduction: Building a model that allows us to summarize a data set with a small number of representative variables that collectively explain most of the variability in the original set e.g.
Association Rules: Apply association rules on given dataset, perform market basket analysis, Detect recurring patterns in data e.g. Identify Product adjacency for Cross-Selling
An Orientation to Reinforcement Learning and Artificial Intelligence
.
Who Should Attend Machine Learning Training
Machine Learning Course Duration
2 days session
Each day 8 hours of sessions
Only on Weekends (Saturday & Sunday)
ADVANCED ANALYTICS 101 - MACHINE LEARNING, ARTIFICIAL INTELLIGENCE AND BIG DATA
What you’ll learn from the Course
AI COURSE Online Outline
Day 1
An overview of Data Science, Machine Learning, Big Data, and Artificial Intelligence Applications.
Basic Concepts and Types of Learning.
Supervised Learning and Techniques in Supervised Learning.
Regression.
Classification
Summarize the topics covered
DAY-2
Recap of Day 1
Unsupervised Learning and Techniques in Unsupervised Learning
Clustering
Dimensionality Reduction
Association Rules
An Orientation to Reinforcement Learning and Artificial Intelligence
Summarize the topics covered
Course Policy:
The charges for trainer’s fees for trainings conducted at Nimap Infotech
Training Center will be shared on enrollment. FOR ENQUIRY: mail to enquiry@nimapinfotech.com
Wire Transfer Details
Bank Name : ICICI bank
Branch : Mazagaon Branch
Account Name : Nimap Infotech LLP
A/c. no :107105000697
IFSC Code : icic0001071
MICR code : 400229073
Training Terms and Conditions
