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Post Graduate Program in Data Science in Chandigarh

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Expedite your Career with Prestigious Post Graduate Program in Data Science | Learn Data Science with India’s #1 course and Get Ahead in Your Career | Learn Extensive use of Tools & Technologies and Analytics Techniques

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Accreditations & Affiliations

Diploma

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Key Features

1-Year Gold Membership

Live Projects + Monthly Brush-up sessions + Recorded Videos + Weekly Job Support + Career Services

9 in 1 Program

Training + Projects + Internship + Certification + Placement + E-Learning + Bootcamps + Hackathons + Gold Membership

25+ Industry Graded Projects

Our Trainers are well versed in the subject matter with 19+ Experience. They Focus on giving Learner Industry Graded Projects, as per the Curriculum during the training for Practical and In-Depth Learning of the Subject Matter

100% Job Assistance and Internship

Weekly Job Support + E-Learning Access + Skill Enrichment Sessions for Interview + 12-month Bootcamps Brush-up Sessions

Capstone Projects

Capstone Projects based on the modules for the Specialization of Knowledge and Skills Gained. This course offers you Specific Capstone Projects for a cumulative understanding of the topic. After the completion of this project, the learner will be termed a Data Scientist

12-Month Program

6 Month Course + 6 Month Internship. The Curriculum is designed by the Industry Expert for Substantial Knowledge on the Subject matter. The Modules are allotted dedicated enough time frame for detailed knowledge of the Course


About the Post Graduate Program in Data Science

Why Data Science?

According to a recent evaluation, more than 93% of the firms use Artificial Intelligence for enhanced products and services

           ● 43% of Professionals in Business Analytics in India have work experience 3 years
           ● 67% Jobs are open for fresher or professional with experience less than 5 years

           ● It is estimated, that by 2022, jobs in  Data Science and analytics arena will have a void   

              of 2.9+ Million jobs   

           ● The Data Science Industry is estimated to be growing with a remarkable rate of 33.7% 

              CAGR (Compound Annual Growth Rate)

           ● It is estimated that India will become one of the Top 5 Leading Markets in Big Data by           

              the end of 2021


“Big Data is at the Foundation of all Mega Trends that are happening”   - Chris Lynch 


Duration

               12 months: 6 Months Course + 6 Months Internship: Instructor-Led Live Online         

                 Classroom Sessions                  

             ● Live Projects for improved understanding of the subject 

             ● Capstone Project as a Culminating Assignment 

             ● Bootcamp sessions for 1 Year


Trainers at Henry Harvin®

              ● Trainers with 23+ experience in the Industry with Global Certification 

              ● Expertise on the Topics and the Tools with expansive Teaching Experience of

                  having trained 897+ Individual Globally                                              

              ● Aspirants are free to attend Multiple Sessions with Multiple Trainers


Become Job Ready

On the Successful Completion of the Post Graduation in Data Science form Henry Harvin® 

Be Exposed to the High Paying Jobs and Fill the Void of 3+ Million Jobs Globally


Alumni Status

Become a part of the elite Analytic Academy of Henry Harvin® & join the 18,000+ strong alumni network worldwide


Learning Benefits Of Data Science

           ● Be well accomplished  in analytics tools and technologies such as Python, Tableau, SQL
          ● Know about the Machine learning techniques such as Regression, Predictive
                Clustering, Time Series Forecasting, Classification, etc.

       ●  Create an analytics framework using statistics and data modeling to structure any 

             Business problem 

       ●  Learn to use  data cleaning and data transformation operations using tools and 

             Techniques

        Learn Comprehensively about  Deep Learning, Natural Language Processing (NLP)

       ●  Be Job-ready for the post of Data Scientist, Data Engineer, or Analyst for top Analytics 

             companies  

       ●  9 in 1 Program: Training + Projects + Internship + Certification + Placement +

          E-Learning +Bootcamps  + Hackathons + Gold Membership

 


Recognitions of Henry Harvin® Education

          ●  Winner of Top Corporate Training Award, Game-Based Learning Company of the Year, 

             under   40 Business World Award       

          ● Affiliated with American Association of EFL, Ministry of Corporate Affairs, MSME, 

             UKAF, UKCert, Project Management Institute (PMI), and ISO 29990:2010 certified.       

          ● Reviews: 1400+ Google Reviews, 200+ Youtube Testimonials with 4.5+ Rating. Rated

             on Goabroad, Trustpilot, Gooverseas & more


Takeaways of Your Investment

         ● 12- Months of  live Online Interactive Classroom Training 

           ●  Be a Post Graduate in Data Science 

           ●  Updated Study Material 

           ●  Recorded Videos of the Session 

           ●  Multiples Sessions with Multiple Trainers 

           ●  1-Year Gold Membership Of Henry Harvin® Analytics Academy 

           ●  Monthly Boot Camps for Brush-up Sessions 

           ●  Access to the Learning Management System 

           ●  Opportunity To Work with Industry Top Brands

 


Know the complete offerings of our Post Graduate Program in Data Science in Chandigarh



Frequently Bought Together

Post Graduate Program in Data Science Curriculum

Programming is an increasingly important skill. This course will establish your proficiency in handling basic programming concepts. This program will help you to gain basic programming concepts like data types, variables, strings, loops, functions, and software engineering concepts like multithreading and multitasking.

Key Learning Objectives

- Achieve fundamental programming knowledge

- Understanding basics of data structures, data types, variables, C++, and JAVA

 

Course Curriculum

- Course Introduction

- Java Foundation

- C++ Foundation

Statistics is the discipline of allocating a prospect through the classification, collection, and analysis of data. A substructure part of Data Science, this Course helps you in defining the statistical terms. The Course explains measures of central tendency and dispersion and comprehended skewness, correlation, regression, distribution. It will enable you to make data-driven predictions through statistics and essential application of it.

Key Learning Objectives 

- Learn the fundamentals of statistics

- Collaborate with different types of data

- How to organize different types of data

- Compute the measures of central tendency, asymmetry, and variability

- Evaluate correlation and covariance

- Distinguish different types of distribution and work on it

- Estimate confidence intervals

- Perform and Evaluate hypothesis testing

- Make data-driven decisions

- Know comprehensively  the mechanics of regression analysis

- Carry out regression analysis

- Use and understand dummy variables

 

Course curriculum 

 

Lesson 1 - Introduction 

Lesson 2 - Sample or Population Data? 

Lesson 3 - The Fundamentals of Descriptive Statistics 

Lesson 4 - Measures of Central Tendency, Asymmetry, and Variability 

Lesson 5 - Practical Example: Descriptive Statistics 

Lesson 6 - Distributions 

Lesson 7 - Estimators and Estimates 

Lesson 8 - Confidence Intervals: Advanced Topics 

Lesson 9 - Practical Example: Inferential Statistics 

Lesson 10 - Hypothesis Testing: Introduction 

Lesson 11 - Hypothesis Testing: Let’s Start Testing! 

Lesson 12 - Practical Example: Hypothesis Testing 

Lesson 13 - The Fundamentals of Regression Analysis 

Lesson 14 - Subtleties of Regression Analysis 

Lesson 15 - Assumptions for Linear Regression Analysis 

Lesson 16 - Dealing with Categorical Data

Lesson 17 - Practical Example: Regression Analysis

 

 

 

 

Gain Substantial Knowledge into the R Programming language with this introductory course. An essential programming language for data analysis, R Programming is a fundamental key to becoming a successful Data Science professional. In this course, you will learn how to write R code, learn about R’s data structures, and create your own functions using R. On completion of this course, you will be able to handle and create data analysis

 

Key Learning Objectives

- Learn about math, variables, and strings, vectors, factors, and vector operations

- Gain fundamental knowledge on arrays and matrices, lists, and data frames

- Get an understanding of conditions and loops, functions in R, objects, classes, and debugging

- Learn how to accurately read the text, CSV, and Excel files. Learn how to write and save data objects in R to a file

- Understand the working of strings and dates in R

 

Course curriculum 

Lesson 1 - R Basics 

Lesson 2 - Data Structures in R 

Lesson 3 - R Programming Fundamentals 

Lesson 4 - Working with Data in R 

Lesson 5 - Handling Data in R

The next step to becoming a data scientist is learning R—the most in-demand open source technology. R is the most powerful Data Science and analytics language, which has a steep learning curve and vigorous community. Data Science with R is becoming the technology of choice for organizations that are adopting the power of analytics for competitive expedience.

Key Learning Objectives 

- Gain a substantial understanding of business analytics

- Install R, R-studio, and workspace setup, and learn about the various R packages

- Master R programming and understand how various statements are executed in R

- Gain an in-depth understanding of data structure used in R and learn to import/export data in R

- Define, understand and use the various apply functions and dplyr functions

- Understand and use the various graphics in R for data visualization

- Gain a basic understanding of various statistical concepts

- Understand and use hypothesis testing method to drive business decisions

- Understand and use linear, non-linear regression models, and classification techniques for data analysis

- Learn and use the various association rules and Apriori algorithm Learn and use clustering methods including K-means, DBSCAN, and hierarchical

clustering

 

Course curriculum 

Lesson 1 - Introduction to Business Analytics 

Lesson 2 - Introduction to R Programming 

Lesson 3 - Data Structures 

Lesson 4 - Data Management in R

Lesson 5 - Advanced Data Visualization

Lesson 6 - Descriptive Statistics in R

Lesson 7 - Regression Analysis 

Lesson 8 - Decision Tree: Classification 

Lesson 9 - Clustering: K-means and Hierarchical

Lesson 10 - Association Rule Analysis

Get ahead with your learning of Python for Data Science with this introductory course and familiarize yourself with programming. Upon completion of this course, you will be able to write your Python scripts, perform fundamental hands-on data analysis using the Spyder/Jupyterbased lab environment.

 

Key Learning Objectives 

- Start creating the First Python program by implementing concepts of variables, strings, functions, loops, conditions

- Understand the modulation of lists, sets, dictionaries, conditions and branching, objects and classes

- Work with data in Python such as reading and writing files, loading, working, and saving data with Pandas

 

Course curriculum 

Lesson 1 - Python Basics

Lesson 2 - Python Data Structures

Lesson 3 - Python Programming Fundamentals

Lesson 4 - Working with Data in Python

Lesson 5 - Working with NumPy Arrays

 

This Data Science with Python course will set up your mastery of Data Science and analytics techniques using Python. In this Python for Data Science course, you will learn the essential concepts of Python programming and gain in-depth knowledge in data analytics, Machine Learning, data visualization, web scraping, and natural language processing

Key Learning Objectives 

- Learn an in-depth understanding of Data Science processes, data wrangling, data exploration, data

   visualization, hypothesis building, and testing Install the required   

- Understand Python environment and other auxiliary tools and libraries

-  Understand the essential concepts of Python programming such as data types, tuples, lists, dicts,

   basic operators, and functions   

- Perform high-level mathematical computing using the NumPy package and its vast library of

    mathematical functions 

- Carry out scientific and technical computing using the SciPy package and its sub-packages such  

    as Integrate, Optimize, Statistics, IO, and Weave      

-   Carry out data analysis and manipulation using data structures and tools provided in the Pandas

    package 

-   Gain an in-depth understanding of supervised learning and unsupervised learning models such as  

   linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline

-   Use the Matplotlib library of Python for data visualization

-   Extract useful data from websites by performing web scraping using Python

 

Course curriculum 

Lesson 1 - Data Science Overview

Lesson 2 - Data Analytics Overview

Lesson 3 - Statistical Analysis and Business Applications

Lesson 4 - Python Environment Setup and Essentials

Lesson 5 - Mathematical Computing with Python (NumPy)

Lesson 6 - Scientific Computing with Python (Scipy)

Lesson 7 - Data Manipulation with Pandas

Lesson 8 - Data Visualization in Python using Matplotlib

The Machine Learning course will make you a Master in Machine Learning, a form of Artificial Intelligence that automates data analysis to enable computers to learn and adapt through experience to do specific tasks without explicit programming. You will learn concepts and techniques, including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms and prepare you for your role with advanced Machine Learning knowledge.

Key Learning Objectives

- Master the concepts of supervised and unsupervised learning, recommendation engine, and time series modeling

- Acquire practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach that includes working on four

major end-to-end projects and 25+ hands-on exercises

- Acquire thorough knowledge of the statistical and heuristic aspects of Machine Learning

- Implement models such as support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-n

means clustering, and more in Python

- Validate Machine Learning models and decode various accuracy metrics. Improve the final models using another set of optimization algorithms, which

include Boosting & Bagging techniques

- Comprehend the theoretical concepts and how they relate to the practical aspects of Machine Learning

- Gain expertise in Machine Learning using the Scikit-Learn package

- Use the Scikit-Learn package for natural language processing

 

Course Curriculum 

Lesson 1 - Introduction to Artificial Intelligence and Machine Learning

Lesson 2 - Data Wrangling and Manipulation

Lesson 3 - Supervised Learning

Lesson 4 - Feature Engineering

Lesson 5 - Supervised Learning Classification

Lesson 6 - Unsupervised Learning

Lesson 7 - Time Series Modeling

Lesson 8 - Ensemble Learning

Lesson 9 - Recommender Systems

Lesson 10 - Text Mining

Lesson 11 - Machine Learning with Scikit–Learn

Lesson 12 - Natural Language Processing with Scikit Learn

 

This Natural Language Processing course will give you a comprehensive detail of the science behind applying Machine Learning algorithms to process large amounts of natural language data. Learn the concepts of statistical machine translation and neural models, deep semantic similarity model (DSSM), neural knowledge base embedding, deep reinforcement learning technique, neural models applied in image captioning, and visual question answering using Python’s Natural Language Toolkit (NLTK).

Key Learning Objectives

- Apply Deep Learning models to solve machine translation and conversation problems

- Implement deep structured semantic models (DSSM) to retrieve information

- Understand deep reinforcement learning techniques applied in Natural Language Processing

- Use neural models applied in image captioning and visual question answering

Course curriculum 

Lesson 1 - Introduction to Natural Language Processing

Lesson 2 - Feature Engineering on Text Data

Lesson 3 - Natural Language Understanding Techniques

Lesson 4 - Natural Language Generation

Lesson 5 - Natural Language Processing Libraries

Lesson 6 - Natural Language Processing with Machine Learning and Deep Learning

Lesson 7 - Speech Recognition Technique

This Tableau training will help you master the various aspects of the program and gain skills such as building visualization, organizing data, and designing dashboards. You will also learn concepts of statistics, mapping, and data connection. Tableau is an essential asset to those wishing to succeed in Data Science.

Key Learning Objectives 

- Learn the concepts of Tableau, become proficient with statistics, and build interactive dashboards

- Master data sources and datable blending, create data extracts and organize and format data

- Master arithmetic, logical, table and LOD calculations and ad-hoc analytics

- Become an expert on visualization techniques such as heat map, treemap, waterfall, Pareto, Gantt chart, and market basket analysis

- Learn to analyze data using Tableau Desktop as well as clustering and forecasting techniques

- Gain command of mapping concepts such as custom geocoding and radial selections

- Master Special Field Types and Tableau Generated Fields and the process of creating and using parameters

- Learn how to build interactive dashboards, story interfaces and how to share your work

 

Course Curriculum

Lesson 1 - Getting Started with Data Visualization and Tableau

Lesson 2 - Working with Tableau

Lesson 3 - Working on Metadata and Data Blending

Lesson 4 - Deep Diving with Data and Connections

Lesson 5 - Creating Charts

Lesson 6 - Adding Calculations to your Workbook

Lesson 7 - Mapping Data in Tableau

Lesson 8 - Dashboards and Stories

Lesson 9 - Visualizations for an Audience

Lesson 10- Integration of Tableau with R and Hadoop

 

 

  • Retail
  • E-commerce
  • Web & Social Media
  • Banking
  • Supply Chain
  • Healthcare
  • Insurance
  • Entrepreneurship /Start-Ups
  • Finance & Accounts
  • Business Communication
  • Preparation for the Interview
  • Presentation Skills


Know the complete offerings of our Post Graduate Program in Data Science in Chandigarh


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Why Henry Harvin for Post Graduate Program in Data Science

Well Structured Curriculum

With Technological Advancement and a healthy Growth Rate in demand for Data Scientists, Data Science is an indispensable component for any firm Across the Globe. At Henry Harvin® we provide the best trainers to train the aspirants with Live Projects for specific topics. The Post Graduation in Data Science Course focuses on all important aspects through Practical Training and Capstone projects. Henry Harvin® rewards the learners with Prestigious Certificate for Post graduation in Data Science identified Globally, with 100% Job Assistance

Placement Assistance

After completion of Post Graduate Program in Data Science And Internship ( 6 months Course + 6 Months Internship) Weekly Job Assistance with Leading Companies of the Industry Complimentary Modules on Resume Writing and Skill Development Guidance on Career Building by Henry Harvin®

Highly Valued LMS

Get 24x7 + Lifetime Access to Web + Mobile-Based App with Abundant Data Sets, Case Studies, Content, Recorded Videos, PPT, and Study Notes

Alumni Status from Henry Harvin®

Join Henry Harvin’s wide network of alumni employed in growing domains all across the globe

Affiliations

Henry Harvin® Education is affiliated with the American Association of EFL, UK Cert, UKAF, MSME & Govt of India.



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Post Graduate Program in Data Science in Chandigarh Training Certification Process

1

Counselling and Registration

Consult one of the Counselors and get into the Right Batch. Register yourself for the Post Graduate Program in Data Science

2

Attend the Training for Post Graduate Program In Data Science

Attend the Instructor-Led Sessions of the Post Graduate Program In Data Science. Go Through the Recorded Sessions, in case you missed any topic or training.

3

Submit Projects Assigned and Commence your 6 Months Internship

Submit the Hands-on Project and Capstone Projects assigned during the training for assessment and get into the Assured 6 Months Internship

4

Get Certified as a Post Graduate in Data Science

Post Completion of the training and Internship, get a Certified as Post Graduate in Data Science from Henry Harvin® Analytics Academy. Post it on Social Media and apply for Internship and Freelancing Projects

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