post graduate program in data science

Post Graduate Program in

Data Science

03 Why Data Science?

04 Hiring Partners

05 Placement Highlights

06 Program Eligibility Criteria and Application Process

07 Data Science Batch Profile

08 About the Program

09 Key Features

10 Program Curriculum

22 Certifications

23 Learning Benefits

24 Career Benefits

25 Our Clientele

26 Media Recognition

27 Reviews & Rankings

28 About Henry Harvin® Education

11 Course 1 - Programming for Non Programmers

12 Course 2 - Statistics for Data Science

13 Course 3 - R Programming for Data Science

14 Course 4 - Data Science with R

15 Course 5 - Python for Data Science

16 Course 6 - Data Science with Python

17 Course 7 - Machine Learning

18 Course 8 - Natural Language Processing

19 Course 9 - Tableau

20 Course 10 - Power BI

21 Capstone Project

Table ofContents

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 or less

It is estimated, that by 2022, jobs in Data Science and analytics arena will have a void of 2.9+ Million jobs

It is estimated that India will become one of the Top 5 Leading Markets in Big Data by the end of 2021

67% Jobs are open for fresher or professional with experience less

than 5 years

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

CAGR (Compound Annual Growth Rate)

03 Why Data Science?

04 Hiring Partners

05 Placement Highlights

06 Program Eligibility Criteria and Application Process

07 Data Science Batch Profile

08 About the Program

09 Key Features

10 Program Curriculum

22 Certifications

23 Learning Benefits

24 Career Benefits

25 Our Clientele

26 Media Recognition

27 Reviews & Rankings

28 About Henry Harvin® Education

Hiring Partners

And 200 more...

Roles Offered

Analytics Consultant

Statistcian

ML Engineer Manager Analytics

Data EngineerData Analyst

Reporting AnalystData Scientist

Research ExecutiveAI Engineer

200+Participating Companies

25 LPAHighest CTC

6.9 LPA+Average CTC

87%Average Salary Hike

Placement Highlights

Summary

Roles Offered

Program Eligibility Criteria and Application Process

Application Process

Eligibility Criteria

Screening call with Alumni/ Faculty

Shortlisted candidates need to appear for an online

aptitude test

Admissions committee will review and shortlist

Apply by filling a simple online application form

For admission to this Post Graduate Program in Data Science, candidates should have:• A bachelor’s degree with an average of 50% or higher marks• Basic understanding of programming concepts and mathematics• Current university students in their final year with an average of 50%• or higher marks can also apply

The application process consists of three simple steps. An offer of admission will be made to the selected candidates and accepted by the candidates by paying the admission fee.

COURSE

Step 1 Step 2 Step 3 Step 4

15% 20% 25% 23% 12%5%

Freshers < 1 Year 1-2 Years 2-3 Years 2-5 Years 5+ Years

Data Science Batch Profile

Experience Distribution

Educational Backgrounds

About the Program

Training 12 Months of Live Online Interactive Classroom Sessions & Guaranteed Internship Projects

Facility to undergo projects in Re-tail, E-Commerce, Web & Social Media, Banking, Supply Chain, Healthcare, Retail, Insurance, En-trepreneurship, Finance & More.

Internship 6-Months Guaranteed Internship to gain practical experience of the learnings

Placement 100% Placement Guarantee Sup-port for 1-Year post successful completion

E-Learning Access with abundant tools and tech-niques, video content, assess-ments, and more

BootcampsRegular Bootcamps spread over the next 12 months

HackathonsFree Access to #AskHenry Hack-athons and Competitions

MembershipGet 1-Year Gold Membership of Henry Harvin® Analytics Acade-my for the Post Graduate Program in Data Science

CertificationDistinguish your profile with the global credential of Post Graduate in Data Science and showcase expertise by using the Hallmark of PGDS next to your name ,along with 10-course completion certif-icates.

9 in 1 Program

08 07

03 04

05 06

02 01

Guaranteed Internship Post Training

Attend Unlimited Batches with Different Instructors for the next 1 year without paying anything extra

Key Features

12+ Bootcamps as part of the #AskHenry series

24x7 Lifetime Support & Access

Mobile App Access to Moodle E-Learning Portal

Access to 5+ Soft Skills courses to enhance employability 09

100% Placement Guarantee Support for 1 Year

1-Year Gold Membership of Henry Harvin® Analytics Academy

Hallmark of PGDS (Post Graduate in Data Science) next to your name For

example: Sahil Kumar (PGDS)

Programming for Non Programmers

Statistics for Data Science

R Programming for Data Science

Data Science with R

Natural Language Processing Tableau

Python for Data Science

Data Science with Python

Power BI

Machine Learning

Capstone Project

Program Curriculum Electives• Artificial Intelligence• Machine Learning with R• C++ Foundation with Data

Structures and Algorithms• Java Foundation with Data

Structures and Algorithms

Programming for Non ProgrammersProgramming 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 Objectivesn Achieve fundamental programming knowledgen Understanding basics of data structures, data types, variables, C++, and JAVA

Course Curriculumn Course Introductionn Java Foundation n C++ Foundation

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Statistics for Data ScienceStatistics 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 Objectivesn Learn the fundamentals of statistics n Collaborate with different types of data n How to organize different types of data n Compute the measures of central tendency, asymmetry, and variability n Evaluate correlation and covariance n Distinguish different types of distribution and work on it n Estimate confidence intervals n Perform and Evaluate hypothesis testing n Make data-driven decisions n Know comprehensively the mechanics of regression analysis n Carry out regression analysis n Use and understand dummy variables

Course Curriculumn Lesson 1 - Introduction n Lesson 2 - Sample or Population Data? n Lesson 3 - The Fundamentals of Descriptive Statistics n Lesson 4 - Measures of Central Tendency, Asymmetry, and Variability n Lesson 5 - Practical Example: Descriptive Statistics n Lesson 6 - Distributions n Lesson 7 - Estimators and Estimates n Lesson 8 - Confidence Intervals: Advanced Topics n Lesson 9 - Practical Example: Inferential Statistics n Lesson 10 - Hypothesis Testing: Introductionn Lesson 11 - Hypothesis Testing: Let’s Start Testing! n Lesson 12 - Practical Example: Hypothesis Testing n Lesson 13 - The Fundamentals of Regression Analysis n Lesson 14 - Subtleties of Regression Analysis n Lesson 15 - Assumptions for Linear Regression Analysis n Lesson 16 - Dealing with Categorical Data n Lesson 17 - Practical Example: Regression Analysis

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R Programming for Data Science

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 struc-tures, and create your own functions using R. On completion of this course, you will be able to handle and create data analysis.

Key Learning Objectivesn Learn about math, variables, and strings, vectors, factors, and vector operations n Gain fundamental knowledge on arrays and matrices, lists, and data frames n Get understanding on conditions and loops, functions in R, objects, classes, and debugging n Learn how to accurately read text, CSV, and Excel files. Learn how to write and save data objects in

R to a file n Understand the working of strings and dates in R

Course Curriculumn Lesson 1 - R Basics n Lesson 2 - Data Structures in R n Lesson 3 - R Programming Fundamentals n Lesson 4 - Working with Data in R n Lesson 5 - Handling Data in R

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Data Science with RThe 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 vig-orous community.Data Science with R is becoming the technology of choice for organizations who are adopting the power of analytics for competitive expedience.

Key Learning Objectivesn Gain a substantial understanding of business analytics n Install R, R-studio, and workspace setup, and learn about the various R packages n Master R programming and understand how various statements are executed in R n Gain an in-depth understanding of data structure used in R and learn to import/export data in R n Define, understand and use the various apply functions and dplyr functions n Understand and use the various graphics in R for data visualization n Gain a basic understanding of various statistical concepts n Understand and use hypothesis testing method to drive business decisions n Understand and use linear, non-linear regression models, and classification techniques for data

analysis n Learn and use the various association rules and Apriori algorithm Learn and use clustering methods

including K-means, DBSCAN, and hierarchical clustering

Course Curriculumn Lesson 1 - Introduction to Business Analytics n Lesson 2 - Introduction to R Programming n Lesson 3 - Data Structures n Lesson 4 - Data Management in Rn Lesson 5 - Advanced Data Visualizationn Lesson 6 - Descriptive Statistics in Rn Lesson 7 - Regression Analysis n Lesson 8 - Decision Tree: Classification n Lesson 9 - Clustering: K-means and Hierarchicaln Lesson 10 - Association Rule Analysis

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Python for Data ScienceGet 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 Objectivesn Start creating the First Python program by implementing concepts of variables, strings, functions,

loops, conditions n Understand the modulation of lists, sets, dictionaries, conditions and branching, objects and

classes n Work with data in Python such as reading and writing files, loading, working, and saving data with

Pandas

Course Curriculumn Lesson 1 - Python Basics n Lesson 2 - Python Data Structures n Lesson 3 - Python Programming Fundamentals n Lesson 4 - Working with Data in Python n Lesson 5 - Working with NumPy Arrays

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Data Science with PythonThis 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 Objectivesn Learn in-depth understanding of Data Science processes, data wrangling, data exploration, data

visualization, hypothesis building, and testing Install the required n Understand Python environment and other auxiliary tools and libraries n Understand the essential concepts of Python programming such as data types, tuples, lists, dicts,

basic operators, and functions n Perform high-level mathematical computing using the NumPy package and its vast library of mathe-

matical functions n Carry out scientific and technical computing using the SciPy package and its sub-packages such as

Integrate, Optimize, Statistics, IO, and Weave n Carry out data analysis and manipulation using data structures and tools provided in the Pandas

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

linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipelinen Use the matplotlib library of Python for data visualization n Extract useful data from websites by performing web scraping using Python

Course Curriculumn Lesson 1 - Data Science Overview n Lesson 2 - Data Analytics Overview n Lesson 3 - Statistical Analysis and Business Applications n Lesson 4 - Python Environment Setup and Essentials n Lesson 5 - Mathematical Computing with Python (NumPy) n Lesson 6 - Scientific Computing with Python (Scipy) n Lesson 7 - Data Manipulation with Pandas n Lesson 10 - Data Visualization in Python using Matplotlib

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Machine LearningThe Machine Learning course will make you 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 Objectivesn Master the concepts of supervised and unsupervised learning, recommendation engine, and time

series modeling n 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

n Acquire thorough knowledge of the statistical and heuristic aspects of Machine Learning n Implement models such as support vector machines, kernel SVM, naive Bayes, decision tree classi-

fier, random forest classifier, logistic regression, K-means clustering and more in Python n Validate Machine Learning models and decode various accuracy metrics. Improve the final models

using another set of optimization algorithms, which include Boosting & Bagging techniques n Comprehend the theoretical concepts and how they relate to the practical aspects of Machine

Learningn Gain expertise in Machine Learning using the Scikit-Learn package n Use the Scikit-Learn package for natural language processing

Course Curriculumn Lesson 1 - Introduction to Artificial Intelligence and Machine Learning n Lesson 2 - Data Wrangling and Manipulation n Lesson 3 - Supervised Learning n Lesson 4 - Feature Engineering n Lesson 5 - Supervised Learning Classification n Lesson 6 - Unsupervised Learning n Lesson 7 - Time Series Modeling n Lesson 8 - Ensemble Learning n Lesson 9 - Recommender Systems n Lesson 10 - Text Miningn Lesson 11 - Machine Learning with Scikit–Learn n Lesson 12 - Natural Language Processing with Scikit Learn

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Natural Language Processing (NLP)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 con-cepts 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 Objectivesn Apply Deep Learning models to solve machine translation and conversation problems n Implement deep structured semantic models (DSSM) to retrieve information n Understand deep reinforcement learning techniques applied in Natural Language Processing n Use neural models applied in image captioning and visual question answering

Course Curriculumn Lesson 1 - Introduction to Natural Language Processing n Lesson 2 - Feature Engineering on Text Data n Lesson 3 - Natural Language Understanding Techniques n Lesson 4 - Natural Language Generation n Lesson 5 - Natural Language Processing Libraries n Lesson 6 - Natural Language Processing with Machine Learning and Deep Learning n Lesson 7 - Speech Recognition Technique

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TableauThis 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 Objectivesn Learn the concepts of Tableau, become proficient with statistics and build interactive dashboards n Master data sources and datable blending, create data extracts and organize and format data n Master arithmetic, logical, table and LOD calculations and ad-hoc analytics n Become an expert on visualization techniques such as heat map, tree map, waterfall, Pareto, Gantt

chart and market basket analysis n Learn to analyze data using Tableau Desktop as well as clustering and forecasting techniques n Gain command of mapping concepts such as custom geocoding and radial selections n Master Special Field Types and Tableau Generated Fields and the process of creating and using

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

Course Curriculumn Lesson 1 - Getting Started with Data Visualization and Tableaun Lesson 2 - Working with Tableau n Lesson 3 - Working on Metadata and Data Blendingn Lesson 4 - Deep Diving with Data and Connections n Lesson 5 - Creating Charts n Lesson 6 - Adding Calculations to your Workbook n Lesson 7 - Mapping Data in Tableau n Lesson 8 - Dashboards and Stories n Lesson 9 - Visualizations for an Audiencen Lesson 10- Integration of Tableau with R and Hadoop

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Power BIThis Power BI training will help you gain expertise on 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. Power Bi is an essential asset to those wishing to succeed in Data Science

Key Learning Objectivesn Develop Intrinsic Understanding of How Table Calculations Workn Create Effective Presentations using Storiesn Easily Implement Advanced Mapping Techniquesn Understand Data/KPIs and Importance of Business Intelligencen Create Highly Interactive Dashboardsn Easily Create Charts of any Typen Connect Power BI to other Sources effortlesslyn Work on Real Life Business Problems Proficiently

Program Curriculumn Lesson 1 - Getting Started with Business Intelligence and Power BIn Lesson 2 - Introduction and Architecture of Power BIn Lesson 3 - Connecting Power BI with Different Data Sourcesn Lesson 4 - Power Query for Data Transformationn Lesson 5 Data Modelling in Power BIn Lesson 6 - Reports and Visualization in Power BIn Lesson 7 - Dashboards and Stories n Lesson 8 - Visualizations for an Audience

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Capstone Project Capstone Projects are hands-on projects that let you apply what you’ve learned in a Specialization to a practical question or problem related to the Specialization topic. In this Section, you will be able to apply all the skills and knowledge acquired throughout the course.

Key Learning Objectivesn Learn about Data Processing and Data Cleaning: You will learn how to handle the data set and manage

it with analytical tools n Applying the correct Models for the projects: Applying all the techniques learnt by understanding the

datan Representing Results: You will be able to write report and represent the outcome of your analysis

RetailActionable insights for improving sales of a consumer durables retailer using POS data analyticsTechniques used: Market Basket Analysis, RFM (Recency-Frequency Monetary) Analysis, Time Series Forecasting

E-commerceCustomer engagement and brand perception of Indian ecommerce and social media approachTechniques used: Text Mining, Kmeans Clustering, Regression Trees, XGBoost, Neural Network

Web & Social MediaTrapping Social Media exchanges on Twitter- A case study of the 2015 Chennai floodsTechniques used: Topic Modeling using 9 Latent Dirichlet Allocation. K-Means & Hierarchical Clustering

BankingCustomer engagement and brand perception of Indian ecommerce- A social media approachTechniques used: Linear Discriminant Analysis, Logistic Regression, Neural Network, Boosting, Random Forest, CART

Supply ChainDeveloping a demand forecasting model for optimizing supply chainTechniques used: Text Mining, Kmeans Clustering, Regression Trees, XGBoost, Neural Network

HealthcarePrediction of user’s mood using smartphone dataTechniques used: Logistic Regression, Random Tree, ADA Boost, Random Forest, KSVM

RetailMarket basket analysis for consumer durablesTechniques used: Market Basket Analysis, Brand Loyalty Analysis

InsurancePersonal insurance digital assistantTechniques used: NLP (Natural Language Processing), Vector Space Model, Latent Semantic Analysis

Entrepreneurship /Start UpsStart-up insights through data analysisTechniques used: Univariate and Bivariate Analysis, Multinomial Logistic Regression, Random Forest

Finance & AccountsVendor invoicing grief projectTechniques used: Conditional Inference Tree, Logistic Regression, CART and Random Forest

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Certifications

Henry Harvin India Education LLP, Building No.B-9 5th Floor, Sector-3, Noida-201301 Ph:+91- 9015 26 6266 | Email:[email protected] | Web: http://www.henryharvin.com

HenryHarvinEducation

April 24th, 2019 To, Abhijit Roy, Sub: Offer letter for Summer Internship Program on Business Analytics Kindly refer to your application for internship at Henry Harvin Education and our subsequent discussions. We would be happy to offer you the position of Business Analytics Associate (Intern) in EP1 for a period of upto two months in our company on the following terms and conditions:

1. A detailed brief on KRAs and scope of work will be given to you post joining. 2. As an intern you are entitled to training on business analytics along with practical exposure

to industry projects simultaneously. 3. You will be governed by the company’s Personnel Policy, Rules of Conduct, Non-

Disclosure Agreement and all other company policies as applicable to you from time to time.

4. You will be expected to join duty in between 10th to 15th June 2019. Business hours begins from 10.30 A.M. onwards.

5. This offer is subject to your background check which company may do pre or post employment and in case of any negativity company may take any necessary disciplinary action which may lead to termination.

6. You are requested to carry the following documents in original at the time of joining for verification and a copy of the same for submission.

a. High School and Senior Secondary Certificates and Mark sheets b. MBA/BE/B.Tech./ME/M.Tech./MCA other relevant qualification certificate(s)

along with mark sheets c. Experience certificate and salary slip from last employer. d. Blood Group. e. Relieving certificate from last employer. f. 3 Passport Size Photographs. g. Form 16 from last employer. h. Photo Identity Proof. i. PAN Number.

Your appointment at Henry Harvin Education will be subject to ratification of the above. We look forward to welcoming you aboard the Henry Harvin India team. Best regards,

P Solanki HR Manager Henry Harvin Education Pinnacle Business Tower-B Building No.B-9, 5th Floor Sector-3, Noida-201301 (UP) http://henryharvin.com

Certificate of Experience This is to certify that Mr.Sai Teja, has worked with us as a Business Development Intern, from April 2020 to May 2020. At the time of leaving, he was competent enough for the role of Business Development. We found Sai Teja to be adaptable, team player, result-oriented, motivated and hardworking. He worked sincerely on the entrusted assignments. We wish him the best of luck in his all future endeavours. Sincerely,

Kounal Gupta CEO Henry Harvin India Education LLP

Certificate of Experience

This is to certify that Mahima Rohatgi, a student of Lovely Professional University, has worked with us as a Data Analyst, on the project titled- “Data Analysis of Jobs Sector in United States on various Job Portals”, from June 2020 to Aug 2020 and at the time of leaving, she was competent enough for the role of Business Analyst.

We found Mahima Rohatgi to be adaptable, team player, result-oriented, motivated and hardworking. She worked sincerely on the entrusted assignments.

We wish them the best of luck in their future endeavours.

Regards,

Preetika Waikhom Human Resources Manager Tutree Inc.

in Era duH cayr tin oe n Hv

CERTIFICATE NO: 6202/IND/2378

THIS IS TO CERTIFY THAT

DATE: 10-12-2020

THATA

CEO®HENRY HARVIN EDUCATION

HENRY HARVIN®

ANALYTICSA C A D E M Y

SUBRAMANYAM RAGHUVAMSIDHAR

CERTIFIED DATA SCIENCE STATISTICIAN (CDSS)

HAS SUCCESSFULLY COMPLETED ALL THE REQUIREMENTS OF THE STATISTICS FOR DATA SCIENCE COURSE




DATE: 10-12-2020

THATA


HENRY HARVIN®



CERTIFIED DATA SCIENTIST- R (CDS- R )

HAS SUCCESSFULLY COMPLETED ALL THE REQUIREMENTS OF THE DATA SCIENCE WITH R COURSE




DATE: 10-12-2020

THATA


HENRY HARVIN®



PROGRAMING FOR NON PROGRAMMERS

HAS SUCCESSFULLY COMPLETED ALL THE REQUIREMENTS OF THE

COURSE




DATE: 10-12-2020

THATA


HENRY HARVIN®


ANAMIKA APTE

CERTIFIED R PROGRAMMING FOR DATA SCIENCE SPECIALIST

(CRDSS)

HAS SUCCESSFULLY COMPLETED ALL THE REQUIREMENTS OF THE R PROGRAMMING FOR DATA SCIENCE COURSE




DATE: 10-12-2020

THATA


HENRY HARVIN®



CERTIFIED MACHINE LEARNING PRACTITIONER- PYTHON (CMLP- P )

HAS SUCCESSFULLY COMPLETED ALL THE REQUIREMENTS OF THE MACHINE LEARNING WITH PYTHON COURSE




DATE: 10-12-2020

THATA


HENRY HARVIN®



CERTIFIED DATA SCIENCE STATISTICIAN (CDSS)

HAS SUCCESSFULLY COMPLETED ALL THE REQUIREMENTS OF THE STATISTICS FOR DATA SCIENCE COURSE




DATE: 10-12-2020

THATA


HENRY HARVIN®



CERTIFIED NLP PRACTITIONER(CNLPP)

HAS SUCCESSFULLY COMPLETED ALL THE REQUIREMENTS OF THE NATURAL LANGUAGE PROCESSING COURSE




DATE: 10-12-2020

THATA


HENRY HARVIN®



CERTIFIED DATA SCIENTIST- PYTHON (CDS- P)

HAS SUCCESSFULLY COMPLETED ALL THE REQUIREMENTS OF THE DATA SCIENCE WITH PYTHON COURSE




DATE: 08-11-2020


CERTIFIED DATA VISUALIZATION SPECIALIST(CDVS)

HAS SUCCESSFULLY COMPLETED ALL THE REQUIREMENTS OF THE TABLEAU TRAINING AND CERTIFICATION COURSE

RAJAT AGRAWAL




DATE: 08-11-2020


CERTIFIED BUSINESS INTELLIGENCE SPECIALIST(CBIS)

HAS SUCCESSFULLY COMPLETED ALL THE REQUIREMENTS OF THE BUSINESS INTELLIGENCE USING POWER BI COURSE

AJEET AGRAWAL

Learning Benefits

Tools Covered

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Gain Knowledge about the primary Programming and basics of Data

Structures, C++, Java

Learn meticulously about the Fundamentals of Statistics and carrying out Regression Analysis

Learn to create Python Program by implementing concepts of Variables, Strings, Function, Loop

Acquire Practical Mastery over Principles, Algorithms, and application of Machine Learning

Acquire extensive knowledge of Analytics Tools such as R, Python, Tableau,

PowerBI, Pandas, dplyr, NumPy, C++,

Gain an in-depth understanding of Data Science Processes, Data

Visualization, and more

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Career Benefits

Exposure to 4+Millions of Jobs in the Arena of Data Science

Be Part of expanding Data Science and Big Data Market

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Get Hired by International Brands like Google, Amazon, JP Morgan, and other top brands in the industry, as a Data Scientist

Be Highly Paid as a Freelancer or as a full-time Professional after the

Successful completion of PGDSAdd the Certification to your CV & LinkedIn Profile withprofessional & Technical development

Earn a Gratifying Certification from Henry Harvin® - Post

Graduate in Data Science

Our Clientele

CORPORATE CLIENTELE

COLLEGE CLIENTELE

160+ Corporates 60+ Colleges

Media Recognition

20+ Media Recognitions

Reviews & Rankings

1400+ Google Reviews 200+ Youtube Video Testimonials

[email protected]

About Henry Harvin® Education

As a competency and career development organization, Henry Harvin® Education develops, enhances, and promotes select skill-sets that are deemed essential to changing times. Embedding ‘Value Creation’ at the core of its vision, Henry Harvin® Education partners with best in industry organizations and empanels domain experts to transform careers of the diverse audience from industry and academia by harnessing the power of skill centric training programs. These programs are carefully handcrafted to deliver tangible output for its learners by creating a distinguished biosphere of the latest learning technologies, effective content, and experienced trainers. Henry Harvin® Education is inspired by the contributions of Mr.Henry Dunster (First President of America’s Oldest University) to the education industry which has sustained for over 400 years.

About Henry Harvin® Analytics Academy

Henry Harvin® Analytics Academy has been setup with an objective to upskill the current technology and management workforce with in-demand analytics skillset. These skills are imparted through action oriented learning solutions that are carefully handcrafted by subject matter experts with extensive industry experience. These learning solutions are delivered using our unique goal-centric pedagogy by select professionals from leading organizations those also empanelled as domain experts with the academy. This enables the academy in achieving its goal of empowering aspiringanalytics professionals to reach their full professional potential. Henry Harvin® Analytics Academy aims to function in its outreach geographies and generate 50,000 employable Analytics professionals till 2030!

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