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The Postgraduate Diploma in Data Science is a thorough and specialised programme offered in distance mode, giving working professionals and students the flexibility to further their education without the limitations of traditional classroom schedules. The duration of the diploma programme may vary as per the institution. The programme is intended to provide individuals with the skills and knowledge necessary to excel in the dynamic field of data science. Big data analytics, machine learning, statistics, and data visualisation are just a few of the many subjects covered in the programme that are fundamental to data science. Theoretical ideas and real-world applications are thoroughly understood by participants.
Enrolling in an distance postgraduate diploma programme in data science can have a number of advantages since it gives students a thorough and specialised education in the discipline. Here are a few benefits:
Flexibility and ConvenienceFlexibility provided by online programmes enables working adults or those with other obligations to complete their academic goals without affecting their daily schedules.
Enhanced Practical Skills A PG Diploma programme in data science places a strong emphasis on case studies, practical projects, and real-world applications, which helps students upgrade their skills and knowledge as per the industry trends.
Professional DevelopmentEarning a new certification in a high-demanding skill increases your marketability, thereby widening your career prospects and salary potential.
Budget-FriendlyThe fee structure of online programmes is affordable plus they do not incur the costs of accommodation and transportation.
Institutions may have slightly different requirements for applicants seeking admission in this programme. These are a few typical qualifying requirements:
A bachelor's degree from an accredited university, or an equivalent, in any subject.
Candidate should have the basic understanding of C/C++ programming.
The admission is done on rolling basis with a fixed deadline for the submission of the application. The admission calender and strcuture is different for each university. Nonetheless, below mentioned is a general overview of the admissions process followed largely:
Create login details to start with the application form.
Fill in the personal details and upload the documents.
The admission cell scrutinises the applications of every candidate.
Pay the non-refundable application fee.
Shortlisted candidates will receive an official admission offer letter.
The admission is done on rolling basis with a fixed deadline for the submission of the application. The admission calender and strcuture is different for each university. Nonetheless, below mentioned is a general overview of the admissions process followed largely:
Academic Documents
Government ID proof
Work Experience
Passport size photographs
Streamlining your academics as per your field of interest makes you more employable in the tough competition of the current market. Let's see how choosing a particular specialisation will benefit you:
Most of the employers prefer candidates with high level of expertise and therefore, candidates who pursue a diploma/degree in their desired specialisation have access to better job opportunities.
Choosing an ideal specialisation will add more credibility to your profile and expand your knowledge thereby helping you understand the market in a better way.
The course structure and subjects can change as per the descretion of the college.
| Semester - 1 | Semester - 2 |
|---|---|
| Foundations of Data Science | Advanced Data Analysis |
| Programming for Data Science | Machine Learning Fundamentals |
| Mathematics for Data Science | Big Data Technologies |
| Database Management | Data Mining and Predictive Modeling |
| Advanced Statistics for Data Science |
| Semester - 3 | Semester - 4 |
|---|---|
| Deep Learning | Emerging Trends in Data Science |
| Natural Language Processing (NLP) | Capstone Project |
| Data Science in Business |
PG Diploma upgrades your knowledge and boosts your employability in the market. Here are a few job roles you can pursue after completing this diploma:
| Job Roles | Job Description |
|---|---|
| Data Scientist | Utilizes statistical methods, machine learning, and programming abilities to extract useful insights and develop data-driven solutions. Evaluates and understands complicated data sets to support corporate decision-making. |
| Machine Learning Engineer | Creates autonomous systems that can learn and make judgments without explicit programming. The role varies as per client and company requirements. |
| Data Analyst | Focuses on studying and analyzing data to offer insightful analysis and interpretation. Frequently uses databases, statistical software, and visualization tools to display findings. |
| Business Intelligence Developer | Creates and implements methods for gathering, processing, and displaying business data. Provides dashboards, reports, and other tools to assist organizations in making wise decisions. |
| Data Engineer | Designs, builds, tests, and maintains the databases and large-scale processing systems of the organization. Specializes in large-scale data handling and processing. |
| Job Roles | Average Annual Salary |
|---|---|
| Data Scientist | ₹ 14.6 LPA |
| Machine Learning Engineer | ₹ 9.5 LPA |
| Data Analyst | ₹ 6.5 LPA |
| Business Intelligence Developer | ₹ 6.6 LPA |
| Data Engineer | ₹ 10.7 LPA |
| Course Name: | Post Graduate Diploma in Data Science |
| Course Type: | PG Diploma |
| Duration: | 1-2 years (depending on the institution) |
| Mode of Learning: | Distance learning |
| Fee Structure: | Average fees for distance Post Graduate Diploma in Data Science range from ₹10,000 to ₹1,00,000, but may vary depending on the university of your choice. |
| Average Salary Offered: | The average salary after distance PG Diploma in Data Science is around ₹8 LPA, but it varies with job roles and industries, and may go up to ₹20 LPA. |
| Job Roles: | Data Scientist, Data Engineer, Machine Learning Engineer, Data Architect, Business Intelligence Developer, Data Analyst, etc. |
