Advanced Diploma in Data Science

Description

Course Name: Advanced Diploma in Data Science

Course Id: ADDS/Q1001.
Eligibility: 10+2 (Higher Secondary).

Objective: To equip learners with advanced tools, techniques, and methodologies for working with big data and complex datasets. To prepare students for careers in data analytics, data engineering, machine learning, and artificial intelligence.

Duration: 370 Hrs (Equivalent to One Year).

Total Credits: 18.

How You will Get Diploma Certificate:

Step 1- Select your Course for Certification.

Step 2- Click on Enroll Now.

Step 3- Proceed to Enroll Now.

Step 4- Fill Your Billing Details and Proceed to Pay.

Step 5- You Will be Redirected to Payment Gateway, Pay Course and Exam Fee by Following Options.

Card(Debit/Credit), Wallet, Paytm, Net banking, UPI and Google pay.

Step 6- After Payment You will get Study Material Login id and Password on your email id.

Step 7- After Completion of  Course Study give Online Examination.

Step 8- After Online Examination you will get Diploma Certificate soft copy(Scan Copy) and Hard Copy(Original With Seal and Sign).

Step 9- After Certification you will receive Prospect Job Opportunities as per your Interest Area.

Online Examination Detail:

• Duration- 120 minutes.
• No. of Questions- 60. (Multiple Choice Questions).
• 10 Questions from each module, each carry 10 marks.
• Maximum Marks- 600, Passing Marks- 40%.
• There is no negative marking in this module.

How Students will be Graded:
S.No.	Marks	Grade
1	91-100	O (Outstanding)
2	81-90	A+ (Excellent)
3	71-80	A (Very Good)
4	61-70	B (Good)
5	51-60	C (Average)
6	41-50	P (Pass)
7	0-40	F (Fail)

Benefits of Certification:

• Government Authorized Assessment Agency Certification.
• Certificate Valid for Lifetime.
• Lifetime Verification of Certificate.
• Free Job Assistance as per your Interest Area.

Syllabus

Introduction to Data Science: Introduction, integrated development environments (IDE), web integrated development environment, hypothesis testing, basic definitions in graphs, drawing centrality in graphs, page rank.

Data Structures and Algorithms: Introduction, singly linked list, doubly linked list, finding the smallest and largest values in the binary search tree, tree rebalancing, bubble sort, factorial of a number, probability search, counting the number of words in a string, determining the first matching character between two strings.

Data Visualization: Introduction, visualizing data: mapping data onto aesthetics, directory of visualizations, visualizing proportions visualizing nested proportions, handling overlapping points, balance the data and the context, visualizing geospatial data.

Data Wrangling: Data wrangling definition, data formats, basic data wrangling, useful commands, other commands and tools.

Classification and Tabulation of Data: Objectives of classification, advantages of tabulation, types of tables, types of graphs, characteristics for a good statistical average, classification of data, types of tables, general precautions for tabulation.

Data Science and Ethical Issues: Introduction, data cleaning, applications of decisions trees, non-linear regression, multiple linear regression, cross-validation, creating a decision tree, data privacy.

Job Opportunities after completion of Advanced Diploma in Data Science course:

Graduates of the Advanced Diploma in Data Science program have a wide array of career opportunities across multiple industries, such as technology, finance, healthcare, retail, and marketing. The data science field is growing rapidly in India due to the increasing importance of data-driven decision-making and advancements in technology like machine learning, artificial intelligence, and big data.

Career Options and Salary Range

1. Data Scientist

• Role: Data scientists analyze and interpret complex data to help organizations make informed decisions. They use programming, machine learning, statistical models, and data visualization tools to extract insights from large datasets.
• Salary:
  • Entry-level: ₹6–₹10 LPA
  • Mid-level: ₹10–₹20 LPA
  • Senior-level: ₹20–₹40 LPA (can go higher in specialized roles or with extensive experience)

2. Data Analyst

• Role: Data analysts focus on collecting, processing, and analyzing data to help organizations understand patterns, trends, and insights. They use statistical tools and software to prepare reports and visualizations.
• Salary:
  • Entry-level: ₹4–₹6 LPA
  • Mid-level: ₹6–₹12 LPA
  • Senior-level: ₹12–₹20 LPA

3. Data Engineer

• Role: Data engineers design and maintain the infrastructure for data generation, collection, and storage. They work with databases, data warehouses, and big data technologies like Hadoop and Spark to ensure the proper flow and management of data.
• Salary:
  • Entry-level: ₹6–₹10 LPA
  • Mid-level: ₹10–₹18 LPA
  • Senior-level: ₹18–₹30 LPA

4. Machine Learning Engineer

• Role: Machine learning engineers build and deploy machine learning models and algorithms that help organizations make predictions, automate tasks, and improve processes. They often work with large datasets and artificial intelligence technologies.
• Salary:
  • Entry-level: ₹7–₹12 LPA
  • Mid-level: ₹12–₹20 LPA
  • Senior-level: ₹20–₹35 LPA

5. Artificial Intelligence (AI) Engineer

• Role: AI engineers create intelligent systems and algorithms that can mimic human behavior and decision-making processes. They apply principles of AI and deep learning to solve complex problems in various sectors.
• Salary:
  • Entry-level: ₹8–₹15 LPA
  • Mid-level: ₹15–₹30 LPA
  • Senior-level: ₹30–₹50 LPA

6. Business Intelligence (BI) Analyst

• Role: BI analysts use data to help organizations make strategic business decisions. They analyze business trends and performance data to create reports and dashboards that inform management decisions.
• Salary:
  • Entry-level: ₹4–₹6 LPA
  • Mid-level: ₹6–₹12 LPA
  • Senior-level: ₹12–₹18 LPA

7. Quantitative Analyst (Quant)

• Role: Quants use advanced mathematical models and statistical techniques to analyze financial markets and make investment decisions. They often work in finance and banking, helping organizations optimize their portfolios.
• Salary:
  • Entry-level: ₹8–₹12 LPA
  • Mid-level: ₹12–₹25 LPA
  • Senior-level: ₹25–₹50 LPA

8. Big Data Engineer

• Role: Big data engineers work with large-scale data processing systems, designing and implementing solutions that allow organizations to handle massive amounts of data. They work with tools like Hadoop, Spark, and NoSQL databases.
• Salary:
  • Entry-level: ₹7–₹12 LPA
  • Mid-level: ₹12–₹20 LPA
  • Senior-level: ₹20–₹35 LPA

9. Data Visualization Specialist

• Role: Data visualization specialists focus on transforming data into graphical representations such as charts, graphs, and dashboards to help organizations understand the story behind the data. They use tools like Tableau, Power BI, and Python libraries (e.g., Matplotlib).
• Salary:
  • Entry-level: ₹4–₹7 LPA
  • Mid-level: ₹7–₹12 LPA
  • Senior-level: ₹12–₹20 LPA

10. Data Consultant

• Role: Data consultants provide expert advice to organizations on how to best utilize their data for business strategy and performance improvements. They may also recommend tools, technologies, and best practices for data management and analysis.
• Salary:
  • Entry-level: ₹6–₹10 LPA
  • Mid-level: ₹10–₹20 LPA
  • Senior-level: ₹20–₹40 LPA

11. Data Governance Manager

• Role: Data governance managers ensure that the organization’s data is accurate, consistent, secure, and compliant with relevant regulations. They develop policies and procedures for managing data and overseeing its quality.
• Salary:
  • Entry-level: ₹8–₹12 LPA
  • Mid-level: ₹12–₹20 LPA
  • Senior-level: ₹20–₹40 LPA

12. Data Architect

• Role: Data architects are responsible for designing the structure and organization of databases, data warehouses, and other data storage systems. They ensure that data is stored in a way that supports effective analysis and retrieval.
• Salary:
  • Entry-level: ₹8–₹15 LPA
  • Mid-level: ₹15–₹25 LPA
  • Senior-level: ₹25–₹45 LPA

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Salary Growth Overview

• Entry-level: ₹4–₹10 LPA (for roles like data analyst, BI analyst, junior data engineer, etc.)
• Mid-level: ₹10–₹20 LPA (for roles like data scientist, machine learning engineer, or data engineer)
• Senior-level: ₹20–₹50 LPA (for experienced roles like senior data scientist, AI engineer, data architect, etc.)

Factors Influencing Salary

1. Experience: More experienced professionals in data science roles command higher salaries due to their deeper expertise in handling complex data problems and tools.
2. Industry: Data science roles in industries like finance, healthcare, and technology often come with higher pay due to the complexity and demand for these skill sets.
3. Skillset: Knowledge of advanced tools and technologies (like machine learning, big data technologies, AI) and proficiency in languages such as Python, R, and SQL can significantly increase earning potential.
4. Location: Cities like Bangalore, Delhi, Mumbai, and Hyderabad generally offer higher salaries due to the concentration of tech companies and startups.

Industry Growth and Job Outlook

The demand for data science professionals in India is expected to continue growing as companies increasingly rely on data to drive business decisions, improve operations, and develop new products. With the rise of artificial intelligence, machine learning, and big data, the job market for skilled data scientists is expanding rapidly. This growth is also fueled by the adoption of data analytics in various sectors, including healthcare, e-commerce, finance, and government.

According to industry reports, India’s data science and analytics market is projected to grow at a compound annual growth rate (CAGR) of around 30% in the coming years, creating even more opportunities for graduates.

Conclusion

Graduates of the Advanced Diploma in Data Science program are well-positioned for lucrative and diverse career paths across industries. The combination of analytical skills, programming knowledge, and business insight allows them to pursue roles that offer excellent salary growth and job stability. With data science being a key driver of innovation and decision-making, professionals in this field can expect long-term demand and career advancement opportunities.