PGP – Data Science and Artificial Intelligence 4.0

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PGP - Data Science and Artificial Intelligence 4.0

COURSE OVERVIEW

Course Access Duration– 123 Hours

Program Plan – Gives in-depth information about what is covered, schedule, different phases involved and Process

Key Take Away – Benefits of the course

Who should attend – Talks about the eligibility criteria, best suited audience, etc.,

Potential Career Growth:- On completion of PGP – Data Science and Artificial Intelligence 4.0 achieve a rewarding career by iibm institute

ABOUT COURSE

  • The PGP – Data Science and Artificial Intelligence 4.0 from IIBM Institute is intended for participants who want to build their careers in Business Analytics.
  • The Program is carefully crafted by distinguished academic and industry professionals to help participants develop a though conceptual understanding of the essentials and advanced topics in Business Analytics.
  • The Program intends for participants to apply the above analytics skills-sets to solve real-world business problems.
  • PGP – Data Science and Artificial Intelligence 4.0 program intends participants to handle a real-world business problem through various tools and methodologies discussed in the curriculum.

Eligibility & Course Access Duration

Eligibility  Course Access Duration 
Eligibility: Fresh Graduates and Experienced Working Professional. 123 Hours

Fees Details

Fee Option Installment-I Installment-II (after 1 Month) Installment-III (after 1 Month) Total Fees
Lump sum Rs.65,000 Rs.65,000
Installment Rs.20,000 Rs.25,000 Rs.25,000 Rs.70,000
Payment Instruction
1. Fees need to be paid in lump sum / first Installment via Cheque or online payment in favor of "IIBM Institute of Business Management".
2. Exam Fees and GST 18% applicable 

**Scroll left and right table for get details.

Course Details

Module 1                                                            2 Hours

Fundamentals of Data Analytics

  • Data Analytics across Domains
  • What is Analytics?
  • Types of Analytics
  • AI vs ML vs DL vs DS

Module 2                                                            4 Hours

Basics concepts in Statistics for Data Analytics

  • Introduction to statistics
  • Central Limit Theorem
  • Measures of Central Tendencies
  • Measures of Sprea
  • Measuring Scales
  • Descriptive Statistics
  • Inferential Statistics

Module 3                                                                      6 Hours

Advanced concepts in Statistics for Data Analytics

  • Types of Distribution
  • Hypothesis Testing
  • Statistical Tests
  • Analysis of Variance
  • Goodness of Fit test
  • Probability Theory for Data Analytics

Module 4                                                                      15 Hours

Python Essential  for Data Science

  • Python Fundamentals and Programming 6 Hours
  • Data Handling with NumPy and Pandas 5 Hours
  • Data Visualization with MatplotLib 2 Hours
  • Advanced Data Visualization with Seaborn 2 Hours

Module 5                                                                      11 Hours

Data Science with Python

  • Introduction To Data Science 2 Hours
  • End to End Data Science 2 Hours
  • Reading data from different Sources 2 Hours
  • Exploratory Data Analysis 2 Hours
  • Data Science: Data Cleaning Feature Engineering 2 Hours
    • Project 1
  • Data Science Fundamentals 1 Hour

Module 6                                                                      20 Hours

Supervised Learning

  • Regression and Classification Algorithms 2 Hours
    • Project 2 1 Hour
  • Linear Regression
    • Project 3 1 Hour
  • Logistics regression 2 Hours
    • Project 4 1 HOur
  • Decision Trees And Ensamble Method 5 Hours
    • Project 4 1 Hour
  • Naive Bayes                                                                  2 Hours
    • Project 5 1 Hour
  • Support Vector Machine ( SVM) 1 Hours
    • Project 6 1 Hour
  • k-Nearest Neighbors (KNN) 2 Hours
    • Project 7

Module 7                                                            9  Hours

Unsupervised Learning

  • Hierarchical Clustering 2 Hours
    • Project 8 1 Hour
  • K Means 2 Hours
    • Project 9 1 Hour
  • Principal Component Analysis(PCA) 2 Hours
    • project 10 1 Hour

Module 8                                                             30 Hours

Artificial intelligence with Python

  • Natural Language Processing Basics 4 Hour
  • Natural Language Processing Advanced 6 Hour
  • Bayesian Methods for Machine Learning (certified completion) 6Hour
  • Reinforcement Learning 10 Hour
  • Artificial Intelligence Cognitive Services in Cloud 4 Hour

Module 9                                                            10 Hours

Tableau

  • Data Analysis
  • Visualization
  • Dashboards & Stories
    • Project 13

Module 10                                                          6 Hours

Introduction to Database

  • Introduction to Databases
  • Basics of SQL
  • Filtering Data using SQL
  • Displaying Data from Multiple tables
  • Grouping Data and Computing Aggregates
  • Subqueries and Nested queries in SQL
  • Correlated Subqueries

Module 11                                                          10 Hours

Castone Project

Who Should Attend 

  • Degree/Diploma graduates
  • This course is designed for the professionals, who wish to make a career in business analytics and have some Knowledge of IT. There are no pre-requisites for this course.
  • Professionals with 2-10 years of experience will be strongly preferred
  • To gain an understanding of how managers use business analytics to formulate and solve business problems and to support managerial decision making.

Potential Career Growth

  • Improving the decision-makingprocess (quality and relevance)
  • Speeding up of decision-making process
  • Better alignment with strategy
  • Realising cost efficiency
  • Improving competitiveness
  • Producing a single, unified view of enterprise information
  • Synchronising financial and operational strategy
  • Increase revenues
  • Sharing information with a wider audience

Some of the companies known for using cutting edge Analytics (in India) are:

  •  Technology leaders: Google, Facebook, Linkedin
  • Banking, Financial Services and Insurance (BFSI):
  • Capital One, American Express, ICICI, HDFC

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Alumni Speaks

Name:-       N.C.RANGANATH

Company:- HDFC LIFE INSURANCE CO. LTD.,

Review:-  It has been my long cherished dream to pursue further education. I have been working in life insurance sector since 1992 and occupied various positions in managerial cadre both in public and private sector. Due to tight work schedule I could not find time to pursue any further courses. Recently I took a sabbatical to become a Fellow of Teach for India for a period of two years. At the same time I also came across IIBM Institute of Business Management and found this valuable online course. The course helped me in getting deeper insight into various areas such as personnel management, financial services and Sales Distribution management besides providing me an opportunity to secure certifications in Six Sigma, Corporate governance and Project Management. Now I feel more empowered with requisite knowledge to take up higher responsibilities not only in insurance industry but also in any industry per se. My Special thanks to IIBM Institute Team.