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Home > Data Science > PG Diploma in Data Science for Working Professionals

PG Diploma in Data Science for Working Professionals
Start your journey in Data Science with our PG Diploma in Data Science. Best suited for working professionals, the program includes 'Manipal's Career Growth Assurance'.
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    9 month diploma, classes on weekends
  • manipal icon
    400 learners
  • manipal icon
    Classes in Bangalore
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9 month diploma, classes on weekends
manipal icon
400 learners
manipal icon
Classes in Bangalore
  • Knowledge
    Partner
    manipal prolearn partner logo
    manipal prolearn partner logo
₹ 371,700
Ask us everything about the program
Ask us everything about the program

PG Diploma in Data Science for Working Professionals

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Overview
  • manipal overview icon
    Diploma from MAHE
    Get diploma from Manipal Academy of Higher Education, an Institute of Eminence.
  • manipal overview icon
    Classroom Session on Weekends
    Apt for working professionals wanting to build or shift to a career in the data science space.
  • manipal overview icon
    Tool Based Learning
    Hands on learning with tools like R, Python, Excel , SQL, NoSQL, Hadoop, Pig, Hive , Apache Spark & Storm.
  • manipal overview icon
    Who Should Attend
    Managers, Analysts, Business Intelligence professionals, Data Science enthusiasts
  • manipal overview icon
    Experiential Learning Model
    The comprehensive curriculum of our Data Science training is taught through videos, reading material, projects, and assignments.
manipal overview icon
Diploma from MAHE
Get diploma from Manipal Academy of Higher Education, an Institute of Eminence.
manipal overview icon
Classroom Session on Weekends
Apt for working professionals wanting to build or shift to a career in the data science space.
manipal overview icon
Tool Based Learning
Hands on learning with tools like R, Python, Excel , SQL, NoSQL, Hadoop, Pig, Hive , Apache Spark & Storm.
manipal overview icon
Who Should Attend
Managers, Analysts, Business Intelligence professionals, Data Science enthusiasts
manipal overview icon
Experiential Learning Model
The comprehensive curriculum of our Data Science training is taught through videos, reading material, projects, and assignments.
About Course

Manipal ProLearn’s PG Diploma in Data Science program is designed to provide you with a broad understanding of the basic and advanced concepts of Data Science. The Data Science training will enable you to implement Big Data techniques using tools using R, Excel, Tableau, SQL, NoSQL, Hadoop, Pig, Hive, Apache Spark and Storm.

What skills you learn

After completing the Data Science diploma, you’ll be considered as a strong and competent data scientist. The course will help you to:

  • Perform data analysis, modelling, predictive analysis, and storytelling through data visualization, which is crucial to business decision-making.
  • Analyze data sets to summarize their main characteristics, often with visual methods with Exploratory Data Analysis
  • Understand and use Big Data technologies as enablers to deploy enterprise information management and solve business problems
  • Learn artificial intelligence and neural network that emphasizes the creation of intelligent machines.
  • Apply the methods, tools and techniques to real-world problems by leveraging technologies such as R, Python, Excel, SQL, NoSQL, Tableau, Hadoop, Pig, Hive, Apache.
  • Apply the methods, tools and techniques to real-world problems by leveraging technologies such as R, Python, Excel, SQL, NoSQL, Tableau, Hadoop, Pig, Hive, Apach, Spark and Storm, and other open source and proprietary products as well.
  • Communicate analytics problems, methods, and findings effectively orally, visually, and in writing. Become more accurate in predicting outcomes without Machine Learning.
  • Cleaning and unify messy and complex data set with Data Scrapping and Data Wrangling
  • Help Companies make critical decisions through analysis, modelling, visualization, etc.
  • Learn the emerging data science of unstructured data analysis and robotic process automation by choosing elective based on your area of interest.

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Who Should Attend this course
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Working professionals with at least two years of work experience, having mathematical, computer science or technical background
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Minimum 50% marks in graduation required along with relevant work experience
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Candidates from other streams (Chemistry, Biology, Commerce, Arts, Media, and BBA) who have scored 50% or above, will have to take an online Technical Aptitude assessment.
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All candidates will have to undertake an English Proficiency test, irrespective of the graduation streams.
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Working professionals with at least two years of work experience, having mathematical, computer science or technical background
manipal icon
Minimum 50% marks in graduation required along with relevant work experience
manipal icon
Candidates from other streams (Chemistry, Biology, Commerce, Arts, Media, and BBA) who have scored 50% or above, will have to take an online Technical Aptitude assessment.
manipal icon
All candidates will have to undertake an English Proficiency test, irrespective of the graduation streams.
Key Features
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In collaboration with Equifax & Big Data University
The data science program is designed in collaboration with industry leaders Equifax & Big Data University.
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Manipal's Career Growth Assurance
Get exposure to 3 real industry projects by companies, 3 networking sessions with industry leaders & lifetime alumni privileges
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Program Structure
The first 3 terms have a mix of theory and labs while the last term is a project term. The last term will be a project of 2 months.
Request a Call Back
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Course Curriculum
1.1 Programming for Data Science
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Introduction to Software and Operating System
Introduction to programming
Control Structures
Functions and Algorithms
Complexity

1.2 Statistical Techniques for Data Science
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Introduction to Statistics
Probability
Sampling
Testing of Hypothesis
Simple Correlation
Regression

1.3 Data Scrapping and Data Wrangling
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Data Scrapping
Data Wrangling
Introduction to Database Management Systems

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

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

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

2.3 Big Data Technologies
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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
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Introduction to AI
Neural Networks
Deep Learning
Deep Learning Models

3.2 Advanced Big Data Technologies
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Understanding Spark
Spark Programming
Real-time Data Stream Analytics

3.3 Transition to Corporate – Behavioral Development Program
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Transition to Corporate Culture
Communication
Spoken Communication
Written Communication
Presentation Skills
Team Work

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