ICRI Campus
Course Description
BCA Data Science is a four-year undergraduate programme that focuses on using various scientific methods and approaches to draw out meaningful data from a big amount of data that is available.
The BCA program from ICRI specializes in Data Science built on Computer Science and Engineering. It is a unique combination of interdisciplinary program work designed for those who seek to become 'Data Scientists'.
The curriculum design and structure are guided both by recent work on the relation of Data Science to the other domains and the need for talent to meet the demands of the data-driven economy of the future. Graduates of the BCA program in Computer Science and Engineering will be uniquely positioned to pursue a career in industry, academia, or research in this rapidly growing and all-pervasive field of Data Science.
The program's focus is on using scientific methods and approaches to extract meaningful insights from large amounts of data. This program covers aspects of Machine Learning, Data Visualization, Programming, Statistics, and Big Data.
The program offered by ICRI is unique as it combines computer science and engineering to specialize in Data Science. The candidate will be provided the latest exposure to developing codes for data science solutions and R as a programming language.
What is Metaverse?
- Step into a virtual world called Metaverse where you can connect with others and interact with digital objects just like in real life.
- The metaverse isn't just for gaming - data scientists can use it to visualize and explore complex data sets in new and innovative ways. With the data analytics market projected to reach $132.9 billion by 2022, the metaverse is set to play a major role in shaping how we understand and analyze data.
- By 2024, the metaverse job market is projected to be valued at a staggering $800 billion, with a prediction of adding 10,000 jobs in the next five years. This highlights the enormous potential for job opportunities in the metaverse industry, as it continues to grow and evolve
Program objectives :
- Design, develop, and maintain machine learning and other data models
- Select, use, and debug existing data models
- Perform statistical and data analyses, often to make decisions about products or projected audiences
- Conduct research to learn more about the field and to improve model accuracy, including meeting with and interviewing experts
- Work in teams to assess project needs and perform tasks
- Data visualization, e.g. using Jupyter Notebooks/Python
- Database management and data quality monitoring
- Data infrastructure systems, which consist of all tools and software needed to collect, store, and analyze datasets Web development
- Communication with multiple teams - marketing, technical, etc.
Industry
Big data operations like data scientists, analytics, big data engineers, big data managers, and data architects have a lot of potential. Data science-related job responsibilities are among the most sought-after tech positions globally at the moment, and they are also among the third-highest paid. Industry projections indicate that by 2026, 11 million new jobs in the field of data science are likely to be created.
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Fun fact: Amazon gets 18-20 job applications per minute and Google receives 3.0 Million job applications per year. One should have certification & demonstrated learning skills to become job ready.
In India, there is a tone of room for data science applications, particularly in 2023 and the years to come. This includes banking, cyber security, financial institutions, education and healthcare sectors, big data organisations, and even small businesses.
There is significant potential for data science applications in India, with the Data Science market slated to reach 16 Billion $ by 2025 and so will the data Science jobs
The Average Starting Salary of Data scientists for freshers is INR 7.0- INR 8 Lacs P.A. and some of the top industries are BFSI, Retail, Technology and Healthcare and companies as diverse as IBM, Amazon, Google, and Netflix recruit data science professionals.
Curriculam
SEMESTER I
- Principal of Electrical and Electronics Technology
- Computer
- Engineering Physics
- Math I
- Programming for Problem Solving
- Introduction to Artificial Intelligence and Machine learning
- Soft Skill I
SEMESTER II
- Application-Based Programming In Python
- Mechanical Workshop
- Engineering Chemistry
- Advanced Physics
- Math II
- Soft Skill II
- Multimedia Application Lab
SEMESTER III
- Building Essential Language
- OOPS Using JAVA
- Data Structures Using C
- Computer Organization and Architecture
- Discrete Structures
SEMESTER IV
- Communication to Conquer
- Data Acquisition
- Advance JAVA Lab
- Environmental Science
- Database Management System
SEMESTER IV
- Introduction to Biology for Engineers
- Applied Statistical Analysis
- Industrial Internship
- Project-Based Learning I
SEMESTER IV
- Computer Networks
- Principles of Operating System
- Project Based Learning
- Management Course
SEMESTER IV
- Data Warehouse
- Software Engineering and Testing Methodologies
- Theory of Computation
- Design and Analysis of the Algorithm
- Project-Based Learning III
- Programme Elective I
- Industrial Internship II
- Open Elective
- Technical Skill Enhancement Course I
What You Will Become ?
Big corporations
Big corporations and SMEs seek professionals who can collect company data, store it, guarantee its security, and treat it appropriately.
Data Analyst -
responsible for collecting, processing, and performing statistical analyses on large datasets to derive insights and make informed business decisions.
Data Scientist -
Responsible for designing and building predictive models, developing algorithms, and using advanced statistical techniques to analyze data and derive insights.
Business Analyst
responsible for identifying business problems, defining requirements, and using data to make recommendations that improve business performance
Data Engineer:
responsible for building and maintaining data pipelines, creating data warehouses, and designing and implementing data storage solutions.
Database Administrator:
responsible for managing and maintaining databases, ensuring data security, and optimizing database performance.
Data Engineer
Data engineers are responsible for designing and building data pipelines and infrastructure to support data analysis.
Machine Learning Engineer:
They work closely with data scientists to build models that can automate decision-making processes.
Where Will You Work ?
Technology
Many tech companies, including startups and large corporations, hire data scientists for various roles such as data analyst, data engineer, machine learning engineer, etc.
Finance
Financial institutions like banks, insurance companies, and investment firms use data science to analyze risk, create investment strategies, and develop fraud detection models.
E-commerce -
Retail and e-commerce companies use data science to predict customer behavior, optimize pricing, and improve customer experience.
Marketing
Marketing companies and agencies use data science to analyze customer behavior, target advertisements, and personalize content.
Automotive Industry -
With data analytics, car companies can analyze their existing customers to identify characteristics that predict a purchase. Big data can also help car companies use insights like past vehicle purchases, online behavior, and demographics to create personalized marketing communications and share relevant content
