PG Diploma in Data Science for Working Professionals

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Overview
  • Diploma from MAHE
    Get diploma from Manipal Academy of Higher Education, an Institute of Eminence.
  • Class on Weekends
    Apt for working professionals wanting to build or shift to a career in the data science space.
  • Tool Based Learning
    Hands on learning with tools like R, Python, Excel , SQL, NoSQL, Hadoop, Pig, Hive , Apache Spark & Storm.
  • Who Should Attend
    Managers, Analysts, Business Intelligence professionals, Data Science enthusiasts
  • Interactive Classroom Sessions
    Learn from experts with a vast experience in delivering data science training programs
Diploma from MAHE
Get diploma from Manipal Academy of Higher Education, an Institute of Eminence.
Class on Weekends
Apt for working professionals wanting to build or shift to a career in the data science space.
Tool Based Learning
Hands on learning with tools like R, Python, Excel , SQL, NoSQL, Hadoop, Pig, Hive , Apache Spark & Storm.
Who Should Attend
Managers, Analysts, Business Intelligence professionals, Data Science enthusiasts
Interactive Classroom Sessions
Learn from experts with a vast experience in delivering data science training programs
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Course Faculty
Faculty, Manipal ProLearn
Experience: 8+ Years

Qualification
B.Tech (Electronics)
More Info
Analytics Consultant & Trainer
Experience: 2+ Years

Qualification
MS (Software Engineering), M.Sc. (Data Science)
More Info
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Course Curriculum
1.1 Programming for Data Science

Introduction to Software and Operating System
Introduction to programming
Control Structures
Functions and Algorithms
Complexity

1.2 Statistical Techniques for Data Science

Introduction to Statistics
Probability
Sampling
Testing of Hypothesis
Simple Correlation
Regression

1.3 Data Scrapping and Data Wrangling

Data Scrapping
Data Wrangling
Introduction to Database Management Systems

1.4 Exploratory Data Analysis

Introduction to Data Science
Introduction to Data Analysis
Descriptive Analysis
Data Cleansing and transformation
Statistical methods applications for dimension reduction

2.1 Machine Learning

Introduction to Machine Learning and Data Science
Classification
Validation Measures
Clustering
Recommendation Systems
Customer Analytics
Time Series

2.2 Data Visualization

Introduction to Data Visualization 30 Hours
Storytelling through data
Visualization & Communication using Data Visualization
Dashboards and Automation
Visualization Product

2.3 Big Data Technologies

Motivation for Big Data
Getting Started with Hadoop Framework
Understanding HBase
Analyzing Data with Hive
Analyzing Data with Pig
Sqoop, Oozie, Impala

3.1 Artificial Intelligence

Introduction to AI
Neural Networks
Deep Learning
Deep Learning Models

3.2 Advanced Big Data Technologies

Understanding Spark
Spark Programming
Real-time Data Stream Analytics

3.3 Transition to Corporate – Behavioral Development Program

Transition to Corporate Culture
Communication
Spoken Communication
Written Communication
Presentation Skills
Team Work

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