MCA Specialization In Data Science
Other Specialization:
Overview
Master of Computer Application (MCA) program with a specialization in Data Science is a cutting-edge course designed to equip students with advanced skills in both computer science and data analytics. Spanning two years, the MCA with Data Science specialization curriculum covers core subjects such as Advanced Programming, Algorithms, Data Structures, Database Management Systems, and Software Engineering, along with specialized modules focusing on data science techniques, machine learning, statistical analysis, big data technologies, and data visualization. Students gain hands-on experience through practical projects, internships, and industry collaborations, applying data science concepts to real-world scenarios and honing their analytical and problem-solving abilities. Our experienced faculty, modern infrastructure, and industry partnerships ensure that students receive a comprehensive education aligned with current industry trends and demands. Graduates of our MCA program with a specialization in Data Science are well-prepared for roles such as Data Scientist, Machine Learning Engineer, Big Data Analyst, Data Engineer, and Business Intelligence Consultant in various sectors including IT, finance, healthcare, and e-commerce. We also provide career counseling, networking opportunities, and placement support to help students succeed in their chosen career paths within the rapidly evolving field of data science and analytics.
Scope of MCA Specialization In Data Science
According to US Bureau of Labor Statistics, The employment outlook for computer and information technology occupations is exceptionally promising, with a projected growth rate significantly higher than the average across all occupations from 2022 to 2032. On average, approximately 377,500 job openings are anticipated each year within these fields. This surge is attributed to both the expansion of employment opportunities and the imperative to fill positions vacated by workers departing these occupations permanently. The robust projection underscores the ongoing demand for skilled professionals in the computer and information technology sectors over the next decade.
Course Structure MCA Specialization In Data Science
Our B.Tech program in Artificial Intelligence and Machine Learning (AI & ML) combines theoretical and practical knowledge, offering a curriculum that covers programming, data structures, machine learning, deep learning, natural language processing, and big data analytics. The program provides a strong foundation in mathematics and statistics, along with specialized AI & ML topics.
The following table outlines the comprehensive course structure of the B.Tech AI & ML program. It is organized into core, elective, interdisciplinary, and skill enhancement components. Each category specifies the type of courses, their descriptions, and the corresponding credits, ensuring a well-rounded academic experience with a balance of foundational knowledge, research exposure, and professional ethics:
| Category | Short Name | Description | Credits |
|---|---|---|---|
| Departmental Core | DC | Discipline Specific Core Courses (DSC) | 35 |
| Departmental Core | DC | Project / Dissertation / Field Study / Survey | 6 |
| Departmental Core | DC | Seminar | 2 |
| Departmental Core | DC | Internship / on Job Experience | 8 |
| Departmental Core | DC | Research Credit Course | 0 |
| Departmental Elective | DE | Discipline Specific Elective Courses(DSE) | 36 |
| Program Linked Core | PLC | Interdeciplinary | 2 |
| Generic Elective | GE | Open courses/Generic Elective (GE) | 0 |
| University Core | UC | Ability Enhancement Courses (AEC) | 2 |
| University Core | UC | Skill Enhancement Courses (SEC) | 0 |
| Value Added Courses common for all UG (VAC) – Non Graded | |||
| University Core | UC | NSS/NCC | 2 |
| University Core | UC | Envionmental Science | 2 |
| University Core | UC | Human Values and Professional Ethics | 2 |
| S.No. | Course Code | Course | L | T | P | Total Credit | Category | Semester |
|---|---|---|---|---|---|---|---|---|
| 1 | CAL811 | Software Engineering | 3 | 0 | 0 | 3 | DC | 1st Sem |
| 2 | CAL817 | Operating System | 3 | 0 | 0 | 3 | DC | 1st Sem |
| 3 | CAL813 | Advance Database Management System | 3 | 0 | 2 | 4 | DC | 1st Sem |
| 4 | CAL812 | Internet and Java Programming | 3 | 0 | 0 | 3 | DC | 1st Sem |
| 5 | CAL815 | Web Technology | 3 | 0 | 2 | 4 | DC | 1st Sem |
| 6 | CAP801 | Java Lab | 0 | 0 | 2 | 1 | DC | 1st Sem |
| 7 | CAL814 | Departmental Elective-1 | 3 | 0 | 2 | 4 | DE | 1st Sem |
| 8 | CAL818 | Departmental Elective-2 | 3 | 0 | 0 | 3 | DE | 1st Sem |
| 9 | EGL805 | Business Writing and Professional Communication | 2 | 0 | 0 | 2 | PLC | 1st Sem |
| S.No. | Course Code | Course | L | T | P | Total Credit | Category | Semester |
|---|---|---|---|---|---|---|---|---|
| 1 | CAL851 | Programming with Python | 3 | 0 | 2 | 4 | DC | 2nd Sem |
| 2 | CAL857 | Data Communication & Computer Networks | 3 | 0 | 0 | 3 | DC | 2nd Sem |
| 3 | CAL853 | Ethical Hacking | 3 | 0 | 0 | 3 | DC | 2nd Sem |
| 4 | CAL855 | Unix and Shell Programming | 3 | 0 | 2 | 4 | DC | 2nd Sem |
| 5 | Departmental Elective-3 | 3 | 0 | 0 | 3 | DE | 2nd Sem | |
| 6 | Departmental Elective-4 | 3 | 0 | 2 | 4 | DE | 2nd Sem | |
| 7 | Departmental Elective-5 | 3 | 0 | 0 | 3 | DE | 2nd Sem | |
| 8 | Departmental Elective-6 | 2 | 0 | 2 | 3 | DE | 2nd Sem | |
| 9 | CAD851 | Minor project | 0 | 0 | 4 | 2 | DC | 2nd Sem |
| S.No. | Course Code | Course | L | T | P | Total Credit | Category | Semester |
|---|---|---|---|---|---|---|---|---|
| 1 | CAL872 | Cryptography and Network Security | 3 | 0 | 0 | 3 | DC | 3rd Sem |
| 2 | CAL889 | Advanced Java programming | 3 | 0 | 2 | 4 | DC | 3rd Sem |
| 3 | Departmental Elective-7 | 2 | 0 | 2 | 3 | DE | 3rd Sem | |
| 4 | Departmental Elective-8 | 2 | 0 | 2 | 3 | DE | 3rd Sem | |
| 5 | Departmental Elective-9 | 3 | 0 | 0 | 3 | DE | 3rd Sem | |
| 6 | Departmental Elective-10 | 3 | 0 | 0 | 3 | DE | 3rd Sem | |
| 7 | SML886 | Professional Ethics | 2 | 0 | 0 | 2 | PLC | 3rd Sem |
| 8 | CAD840 | Seminar – Research Paper | 0 | 2 | 0 | 2 | DC | 3rd Sem |
| S.No. | Course Code | Course | L | T | P | Total Credit | Category | Semester |
|---|---|---|---|---|---|---|---|---|
| 1 | CAD895 | Internship and Project Work | 0 | 0 | 12 | 6 | DC | 4th Sem |
| 2 | CAD897 | Dissertation | 0 | 0 | 8 | 4 | DC | 4th Sem |
| Course Code | Course | L | T | P | Credit |
|---|---|---|---|---|---|
| CAL814 | Open Source Technologies | 3 | 0 | 2 | 4 |
| CAL818 | Cloud Computing | 3 | 0 | 0 | 3 |
| CAL854 | Artificial Intelligence | 3 | 0 | 0 | 3 |
| CAL852 | ASP .Net with C# | 3 | 0 | 2 | 4 |
| CAL856 | Analysis and Design of Algorithm | 3 | 0 | 0 | 3 |
| CAL859 | R Programming for Data Analysis | 2 | 0 | 2 | 3 |
| CAL873 | Application Development with Android | 2 | 0 | 2 | 3 |
| CAL875 | Digital Marketing Analytics and SEO | 2 | 0 | 2 | 3 |
| CAL874 | Cluster and Grid Computing | 3 | 0 | 0 | 3 |
| CAP878 | Cyber Crime and Digital Forensics | 3 | 0 | 0 | 3 |
Department
at a Glance
- Mission
- Faculty
- Curriculum Highlights
- Facilities and Resources
- Student Organizations and Activities
Exclusive
Labs
- Microsoft Innovation Center
- Microsoft - Global Technical Support Center (GTSC)
- IBM Software Lab For Emerging Technologies
- Oracle Academy Lab
- Unisys Innovation Labs
Your Department in a Nutshell
- Achievements
- Patents
- Research
- Expert Sessions
- Activities
- Labs
Admission Criteria
- Through Eligibility & Scholarship Test (CPU-EST). For details, Click Here
- Rolling Admission: We follow rolling admission process. To apply Click Here
Fee Details
Course Fee | |
|---|---|
Admission Fee (one time) | 5000/- (at the time of admission) |
Tuition Fee | 37000/- Per Semester |
Examination Fee | 3000/- Per Semester |
Development Fee | 3000/- Per Semester |
Caution Money (one time) | 3000/- (Refundable) |
Scholarship Criteria
Based on performance in qualifying exam
| % in Qualifying Class [1] | Scholarship on Tuition Fees | |
|---|---|---|
| Above 90% | 20% | |
| 85% – 89.99% | 10% | |
| 75% – 84.99% | 5% | |
- Early Admission Benefits Upto Rs. 3000/- Admission Taken Before 15th July 2024
- Scholarship in Tuition fee (for all 4 semesters): up to 20% based on academic performance.
Why Join MCA Specialization In Data Science?
Joining an MCA specialization in Data Science offers numerous compelling reasons:
- High Demand: Data Science is one of the fastest-growing fields in the technology industry. There is a significant demand for professionals who can analyze large datasets, derive meaningful insights, and make data-driven decisions across various sectors such as finance, healthcare, e-commerce, and marketing.
- Lucrative Career Opportunities: Data scientists and data analysts are in high demand and command attractive salaries. By pursuing an MCA specialization in Data Science, you open doors to a wide range of career opportunities in industries where data-driven decision-making is crucial.
- Growing Importance of Big Data: With the exponential growth of data generated by businesses and organizations, there is a growing need for skilled professionals who can harness the power of big data technologies and analytics tools to extract valuable insights and drive innovation.
- Versatility and Flexibility: A specialization in Data Science equips you with versatile skills that are applicable across various domains and industries. Whether you are interested in finance, healthcare, retail, or technology, the principles and techniques of data science are relevant and applicable.
- Impactful Contributions: Data scientists play a vital role in helping organizations make informed decisions, optimize processes, improve efficiency, and identify new opportunities. By mastering the tools and methodologies of data science, you can make meaningful contributions to your organization's success and societal advancements.
What makes Department
of MCA Specialization In Data Science unique?
The Department of MCA Specialization in Data Science stands out due to several unique characteristics:
Placements
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Our Students Speak
Package: 3.5 LPA
How to Apply
Steps to Follow
Frequently Asked Questions
MCA Specialization In Data Science at Career Point University
The MCA Specialization in Data Science program at Career Point University typically spans over two years, divided into four semesters.
The eligibility criteria for admission to the MCA Specialization in Data Science program at Career Point University generally include completing a bachelor’s degree in computer applications, computer science, or a related field from a recognized university with a minimum specified percentage as per university guidelines.
The curriculum of the MCA Specialization in Data Science program at Career Point University covers a broad range of subjects including statistics, machine learning, big data technologies, data visualization, database management, and programming languages such as Python and R.
Career Point University may offer elective courses or specialization tracks within the MCA Specialization in Data Science program, allowing students to focus on specific areas such as machine learning, data engineering, business analytics, or natural language processing.
Yes, the MCA Specialization in Data Science program at Career Point University emphasizes practical training, hands-on experience, and project work. Students have the opportunity to work on real-world data science projects, analyze datasets, develop machine learning models, and gain practical exposure to data science tools and technologies.
Graduates of the MCA Specialization in Data Science program at Career Point University can pursue various career opportunities in the field of data science, including roles such as data scientist, machine learning engineer, data analyst, business intelligence analyst, data engineer, and big data architect.
Career Point University provides support for internships, job placements, and career counseling services to help students explore internship opportunities, develop job search skills, prepare for interviews, and secure employment in reputable organizations within the data science industry.
Yes, Career Point University encourages research and innovation within the MCA Specialization in Data Science program. Students have opportunities to engage in research projects, collaborate with faculty members on cutting-edge research initiatives, and contribute to advancements in the field of data science.