Post Graduate Diploma in Data Science


Post Graduate Diploma in Data Science | PGDDS Course Details

Course Overview

Course

Post Graduate Diploma in Data Science

Duration of course

9 months

Objective of Course

To provide in-depth knowledge concerning what is covered, schedule, different phases involved and the process.

For Whom

Those who see their career as data analyst professionals.

Why choose this course

To accelerate your career in data science and for the exponential growth of the country.


About Course

Post Graduate Program in Data science is a nine-month part-time course that aims to equip graduates for a career as a data scientist in the business world for entrepreneurship, public policy or even academia.

This multidisciplinary course attempts to extract knowledge or insights from data in multiple forms and employs techniques and theories within the deep areas of mathematics, statistics, operations research, information science, and computer science.

The purpose of the Post Graduate Program in Data Science is to introduce participants to the tools and techniques employed for administering, managing, analyzing and evaluating data.

Data Science curriculum also equips students with the business realm knowledge so they can add significance as data analyst professionals for the next generation.

PGDDS course provides an extremely unique opportunity to acquire first-hand knowledge about both the theoretical and practical aspects.

This field offers exciting new areas that combine scientific analysis, statistical knowledge, substantive expertise, and computer programming.

With the increasing significance of data science, the growth and importance of data scientists have increased a lot. Data Science is working as the tomorrow of Artificial Intelligence. The students who are interested in analytics, technology firms, regulators, consulting and universities across the globe must go for Post Graduate Diploma in Data Science course. In the present scenario, certain data scientists professionals are now essential parts of brands, businesses, public agencies, and non-profit organizations.

Why Data Science is Important?

Data science is a vast concept that can add value to any company’s data well. It has turned into a basic requirement for almost every organization. Data science is worthwhile for any corporation in any industry. From statistics and insights across workflows and chartering new candidates, to assisting senior staff to create better-informed decisions.

Here Are The Top Reasons Behind The Significance Of Data Science:-

➤ Empowering management and directors or managers to make better decisions

➤ Big Data is a new discipline that is constantly growing and evolving.

➤ Challenging the staff to embrace best practices and focus on issues that really matter.

➤ Decision making must be done with quantifiable and data-driven pieces of evidence.

➤ Examining certain decisions

➤Identifying future opportunities

➤Identification and refining of appropriate target audiences

➤Executing a prime role in the functioning and growth process of brands.

➤Recruiting the right talent for the company.

➤Striving operations and actions based on trends which helps to set company goals.

Eligibility Criteria for PGDDS Course:-

PGDDS programme mainly aims to develop more skills and knowledge of Data Science to do statistical analyzing to support the decision-making process. The working professionals in IT / Analytics / Statistics / Big Data / Machine can apply for this course to acquire in-depth knowledge of this field.

Candidates need to go through the directed eligibility criteria before taking admission in this course:-

  • For enrolling admission in Post Graduate Diploma in Data Science, aspirants must have scored at least aggregate marks of 50 % in  BE / B.Tech / BCA / MCA / B.Sc. (Maths) / M.Sc (Maths) courses.
  • Candidates acquiring Mathematics, Engineering, Statistics, and IT background will be given more preference.
  • Two-year full-time work experience is required after graduation or post-graduation courses.
  • There is a relaxation in the work experience for meritorious fresher students / Young Professionals securing (CGPA > 7/10) marks on the basis of the application.
  • Students completing their final year of graduation are also eligible for this course.
  • There are no restrictions on the age limit for pursuing PGDDS.
Essential Skills And Traits Required For This Course:-

Becoming a Data Scientist is not an easy job, it takes a lot of diligence, patience, and determination to scale up this high profile job. One need to have both the technical and non-technical skills to achieve this profession.

Here are some essential attributes and skills that every data scientists should possess:

Technical Skills:-

➤ Education and training

➤ Work experience

➤ Coding

➤ Proficiency in Mathematics and Statistics

➤ Machine learning, deep learning

➤ Knowledge of analytical tools

➤ Big Data

➤ Data Ingestion

➤ Data architecture

➤ Adept at working with unstructured data

Non- Technical Skills:

➤ Critical Thinking

➤ A strong business acumen

➤ Great communication skills

➤ Strong data intuition

➤ Risk analysis

➤ Problem-solving and good business understanding

PGDDS Course Structure:-

PGDDS course intends to equip students with an introduction of data science approach, quantitative analysis of data using various techniques of statistical learning, a procedure combining classical statistical methods with current advances in computational and machine learning.  In this programme, you will learn Machine Learning, Business Analytics – Applied Modelling and Prediction, Elements of Econometrics, and Information Systems Management.

The course is divided into the following modules to cover up the whole syllabus in 9 months :

1- Information Systems Management:-

This module of PGDDS Course helps the students to learn the management of information systems in organizations that tend to influence the design, configuration, and implementations of Information and Communication Technologies (ICTs). With the basic postulates of project management and governance, it also summarizes the common techniques and the tools associated with ICT management. This module provides an overall view of the benefits management and information systems strategy arrangement. The topics under this module include:

➣ Education and principles of information systems management

➣ Managing information systems projects and designs

➣ Learning of Information systems and benefit management

2- Machine Learning:-

In this module, students study a wide array of models and algorithmic machine learning techniques demonstrated in several real-world applications and datasets. Scholars also obtain a theoretical basis of the methodology. The topics covered in this module are:

➣ Linear regression and regularisation (via least squares and maximum likelihood)

➣ Bayesian Inference

➣ Classification

➣ Resampling methods

➣ Clustering

➣ Non-linear models

➣ Tree-based methods

➣ Support Vector Machines

➣ Random forests

➣ Gaussian Processes

3- Elements of Econometrics:-

This module develops a broad understanding of econometrics to equip students to identify and evaluate several applied analysis of cross-sectional data and to autonomously undertake such analysis by their own. Some of the topics include here as follows:

➣ Random variables and sampling theory

➣ Simple regression analysis

➣ Properties of the regression coefficients

➣ Multiple regression analysis

➣ Transformation of variables

➣ Dummy variables

4- Business Analytics, Applied Modelling, and Prediction:-

The module prepares students to apply modelling at different levels of the management process, learn basic principles of complex variated datasets analysis-extracting associated data, and be able to illustrate the wide use of mathematical models, identifying the limitations and possible misuse. The topics covered here are:

➣ Introduction to data analysis and decision-making

➣ Time series data

➣ Outliers and missing values

➣ Pivot tables

➣ Probability Distributions

➣v Decision making under uncertainty

➣ Methods for selecting random samples

➣ Nonparametric tests

➣ Stepwise regression

➣ Time series forecasting

➣ Regression-based trend models

➣The random walk model

➣ Autoregressive and moving average models

➣ Exponential smoothing

➣ Seasonal models

➣Introduction to linear programming

➣ Product mix models

➣ Sensitivity analysis

➣ Monte Carlo simulation

➣ Applied simulation examples

Admission Process for PGDDS Course:-

Students who are interested in enrolling admission in Post graduation Diploma in Data Science (PGDDS)  must have a bachelor's degree or equivalent with a minimum of 50% in aggregate marks from any recognized Indian university.

Candidates need to fill the application form of the particular college/university from where they want to take admission.

➣ Personal Interview or screening call is done by the directors of the respective college on the basis of the profile of the candidates.

➣After that, the applications forms are then submitted to the admission committee of college in order to complete the admission procedure.

➣ Finally, aspirants will be shortlisted on the basis of their profile and personal interview given.

➣ The shortlisted candidates will be intimated through their registered email or messages.

Career Prospect after PGDDS course:-

With the continuous growth of the Industries, the demand for Data Analytics professionals has also increased over the last few years. According to the survey of companies, Data Scientists are the future of the world today. More than 70 % of companies data survey says that the requirement of these professionals will grow exponentially and the recruiting of Data Professionals will start soon globally. They will soon turn into an integral part of the organization and will assist the world to face major global challenges.  That’s the only reason why the importance of Post Graduate Diploma in Data Science course is increasing day by day across the world.

Data Science is a tangible domain that has far-reaching implications in other fields including healthcare, energy, and education by helping people to experience life, products, and services in a brand new manner. The healthcare industry is the topmost field that is getting 100 % benefit by Data Science and is steadily growing over years. Data science helps them to provide better care for patients at all stages. The second field that truly gets benefited from data science is education. The emerging technologies like smartphones, PCs, and laptops are becoming an integral part of the education system as it provides better opportunities to help students study and enhance their knowledge in an effective manner.

This simply means that data scientists have come up with an ample range of solutions to meet challenges across all sectors. Candidates with PGDDS can attain lucrative career ahead as there are numerous companies across the world who are recruiting the Data Analytics professionals with optimum salary packages. These professionals can work in the following job profiles in an organization:

➣ Financial Analytics,

➣ Data Analyst / Scientist

➣ Marketing: Managers,

➣ Market Research Analyst and Specialist,

➣ Research Scientist etc.

Top Recruiting Companies:-

Here are top recruiting companies that hire Data Analyst professionals after Post Graduate Diploma in Data Science:

➣ Google

➣ Amazon

➣ Wipro

➣ Infosys

➣ Book my show

➣ Walmart

➣ Zomato

➣ Browserstack, etc.

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