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BACHELOR-OF-SCIENCE-MATHEMATICS-STATISTICS-COMPUTER-SCIENCE in General at Al-Ameen Institute of Information Sciences
Bengaluru, Karnataka
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About the Specialization
What is General at Al-Ameen Institute of Information Sciences Bengaluru?
This Bachelor of Science program in Mathematics, Statistics, and Computer Science at Al-Ameen Institute of Information Sciences focuses on providing a robust interdisciplinary foundation. It integrates quantitative reasoning, data analysis, and computational skills, preparing students for the rapidly evolving tech and analytics sectors in India. The program emphasizes a holistic approach to problem-solving using mathematical rigor, statistical inference, and computational implementation.
Who Should Apply?
This program is ideal for fresh graduates from the science stream seeking entry into data science, machine learning, or quantitative finance roles. It also suits individuals passionate about research or higher studies in fields like AI, bioinformatics, or actuarial science. Students with strong analytical aptitude and a keen interest in applying computational methods to complex data problems will thrive.
Why Choose This Course?
Graduates of this program can expect diverse India-specific career paths in data analytics, software development, business intelligence, and research. Entry-level salaries typically range from INR 3.5 to 6 LPA, with significant growth potential in companies like TCS, Infosys, Wipro, and various startups. The interdisciplinary nature also provides a strong foundation for professional certifications in data science or financial modeling.
Student Success Practices
Foundation Stage
Build Strong Fundamentals in All Three Disciplines- (Semester 1-2)
Dedicate equal time to understanding core concepts in Mathematics, Statistics, and Computer Science. Focus on mathematical proofs, statistical derivations, and basic programming logic (C/Java). Utilize online platforms for problem-solving in each area to reinforce theoretical knowledge.
Tools & Resources
NCERT textbooks (for fundamental clarity), Khan Academy, NPTEL courses for Math/Stats/CS basics, HackerRank for C programming practice
Career Connection
A solid foundation is crucial for advanced topics and is highly valued by recruiters for entry-level technical and analytical roles.
Cultivate Logical Thinking and Problem-Solving Skills- (Semester 1-2)
Regularly solve logical puzzles and programming challenges. Participate in college-level coding contests and math olympiads. Engage in peer learning groups to discuss different approaches to complex problems and enhance collaborative problem-solving abilities.
Tools & Resources
GeeksforGeeks for algorithms, CodeChef/LeetCode for competitive programming, Project Euler for mathematical problems
Career Connection
These skills are directly transferable to software development, data analysis, and quantitative research roles, improving interview performance and job readiness.
Develop Effective Study Habits and Time Management- (Semester 1-2)
Implement a disciplined study schedule that balances theory and practical sessions across all three subjects. Focus on active recall and spaced repetition for better retention. Prioritize consistent attendance and active participation in classes.
Tools & Resources
Pomodoro Technique, Google Calendar for scheduling, Note-taking apps like Notion or OneNote
Career Connection
Efficient study habits ensure academic excellence, which is a key criterion for internships, higher studies, and placements in top companies.
Intermediate Stage
Engage in Interdisciplinary Projects and Practical Applications- (Semester 3-4)
Seek opportunities to work on mini-projects that combine elements of Mathematics, Statistics, and Computer Science. For example, build a simple data analysis tool or a statistical model using a programming language. This bridges theoretical knowledge with real-world application.
Tools & Resources
Python with libraries like NumPy, Pandas, Matplotlib, R for statistical analysis, GitHub for version control
Career Connection
Practical projects demonstrate your ability to apply learned concepts, making your profile more attractive for internships and entry-level positions in data science and analytics.
Gain Industry Exposure through Workshops and Certifications- (Semester 3-5)
Attend workshops and seminars on emerging technologies like Machine Learning, AI, or Big Data. Pursue online certifications in relevant tools or areas such as SQL, Python for Data Science, or specific statistical software to deepen your technical skill set.
Tools & Resources
Coursera, NPTEL, Udemy for online courses, Industry events and tech meetups in Bengaluru
Career Connection
Certifications and industry exposure showcase proactive learning, which is critical for securing internships and distinguishing yourself in a competitive job market.
Network and Participate in Academic Competitions- (Semester 3-5)
Connect with faculty, alumni, and industry professionals through college events, LinkedIn, and professional platforms. Participate in hackathons, data science challenges (e.g., Kaggle), or intercollegiate quizzes to test your skills and expand your network.
Tools & Resources
LinkedIn for professional networking, Kaggle for data science competitions, College career services
Career Connection
Networking opens doors to mentorship, internship opportunities, and valuable career insights. Competition success highlights your capabilities to potential employers.
Advanced Stage
Undertake Internships and Advanced Project Work- (Semester 5-6)
Secure internships in data science, software development, or analytics roles to gain hands-on industry experience. For your final year project, choose a topic that deeply integrates all three disciplines and contributes to a real-world problem or research area.
Tools & Resources
Internshala, LinkedIn Jobs for internships, College''''s placement cell support, Research papers for project ideas
Career Connection
Internships are often a direct path to full-time employment. A strong final project showcases your expertise and readiness for challenging roles.
Focus on Placement Preparation and Interview Skills- (Semester 5-6)
Begin rigorous preparation for placement drives, focusing on aptitude, logical reasoning, programming, and subject-specific knowledge. Practice group discussions and mock interviews. Tailor your resume and cover letters for specific job roles.
Tools & Resources
Aptitude books, Mock interview platforms, Company-specific interview guides on Glassdoor/AmbitionBox
Career Connection
Thorough preparation significantly increases your chances of securing placements in desired companies, leading to a successful career launch.
Explore Post-Graduation Options and Career Planning- (Semester 6)
Research options for higher studies in India or abroad (e.g., M.Sc. in Data Science, MBA with Business Analytics). Understand diverse career paths, including research, entrepreneurship, or specialized technical roles, and plan your skill development accordingly.
Tools & Resources
GRE/CAT/GMAT preparation materials, Education counsellors, Alumni network for guidance
Career Connection
Strategic career planning ensures you make informed decisions about your future, whether it''''s pursuing advanced degrees or specializing in a high-demand industry niche.
Program Structure and Curriculum
Eligibility:
- Pass in 10+2 / PUC II (Science stream) or equivalent examination from a recognized board with Mathematics as one of the subjects.
Duration: 3 years (6 semesters)
Credits: 120 credits (as per NEP for 3-year Bachelor degree) Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| LANG101 | Language 1 (e.g., Kannada/Hindi) | Compulsory Language | 3 | Basic Communication, Grammar, Reading Comprehension, Writing Skills, Cultural Aspects |
| ENG101 | English Language | Compulsory Language | 3 | Functional English, Grammar and Usage, Writing Paragraphs, Short Stories, Poetry |
| BSCSC101 | Computer Science – Fundamentals of Computer Science & Problem Solving Techniques | Major Core | 4 | Introduction to Computers, Number Systems, Algorithms and Flowcharts, C Language Basics, Control Statements, Functions and Arrays |
| BSMAT101 | Mathematics – Differential Calculus, Integral Calculus, and Vector Algebra | Major Core | 4 | Successive Differentiation, Partial Differentiation, Beta and Gamma Functions, Multiple Integrals, Vector Differentiation, Vector Integration |
| BSSTA101 | Statistics – Descriptive Statistics and Probability | Major Core | 4 | Data Collection and Presentation, Measures of Central Tendency, Measures of Dispersion, Correlation and Regression, Probability Theory, Random Variables |
| AECC101 | Ability Enhancement Compulsory Course (e.g., Indian Constitution & Human Rights) | AECC | 2 | Constitutional Framework, Fundamental Rights, Human Rights, Directive Principles, Judiciary in India |
| SEC101 | Skill Enhancement Course (e.g., Digital Fluency) | SEC | 2 | Computer Fundamentals, Operating Systems Basics, Internet and Web Browsing, Cyber Security Basics, Digital Tools |
| VC101 | Vocational Course (e.g., Office Automation) | Vocational | 2 | Word Processing, Spreadsheets, Presentations, Database Management, Office Tools |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| LANG201 | Language 1 (e.g., Kannada/Hindi) – II | Compulsory Language | 3 | Advanced Grammar, Short Stories, Essays, Vocabulary Building, Report Writing |
| ENG201 | English Language – II | Compulsory Language | 3 | Communication Skills, Business English, Technical Writing, Literary Analysis, Public Speaking |
| BSCSC201 | Computer Science – Data Structures and Algorithms | Major Core | 4 | Introduction to Data Structures, Arrays and Pointers, Stacks and Queues, Linked Lists, Trees and Graphs, Searching and Sorting |
| BSMAT201 | Mathematics – Differential Equations, Linear Algebra and Solid Geometry | Major Core | 4 | First Order Differential Equations, Second Order Differential Equations, Matrices and Determinants, Eigenvalues and Eigenvectors, Planes and Lines, Spheres, Cones, Cylinders |
| BSSTA201 | Statistics – Probability Distributions and Statistical Inference | Major Core | 4 | Discrete Probability Distributions, Continuous Probability Distributions, Sampling Distributions, Point and Interval Estimation, Hypothesis Testing, Parametric Tests |
| AECC201 | Ability Enhancement Compulsory Course (e.g., Environmental Studies) | AECC | 2 | Natural Resources, Ecosystems, Biodiversity, Pollution and Control, Environmental Ethics |
| SEC201 | Skill Enhancement Course (e.g., Web Designing) | SEC | 2 | HTML Fundamentals, CSS Styling, JavaScript Basics, Web Page Layout, Responsive Design |
| VC201 | Vocational Course (e.g., Data Entry Operator) | Vocational | 2 | Data Entry Techniques, Data Accuracy, Spreadsheet Data Handling, Database Entry, Data Validation |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BSCSC301 | Computer Science – Object Oriented Programming with JAVA | Major Core | 4 | OOP Concepts, Java Basics and Syntax, Classes and Objects, Inheritance and Polymorphism, Packages and Interfaces, Exception Handling |
| BSMAT301 | Mathematics – Real Analysis and Group Theory | Major Core | 4 | Real Number System, Sequences and Series, Limits and Continuity, Differentiability and Mean Value Theorems, Groups and Subgroups, Permutation Groups |
| BSSTA301 | Statistics – Sampling Techniques and Design of Experiments | Major Core | 4 | Simple Random Sampling, Stratified and Systematic Sampling, Sampling and Non-sampling Errors, Analysis of Variance (ANOVA), Completely Randomized Design (CRD), Randomized Block Design (RBD) |
| OE301 | Open Elective (e.g., Introduction to Data Science) | Elective | 3 | Data Science Fundamentals, Data Collection, Data Cleaning, Data Visualization, Basic Machine Learning, Ethical AI |
| SEC301 | Skill Enhancement Course (e.g., Statistical Data Analysis Using R) | SEC | 2 | R Environment, Data Input and Output, Data Manipulation, Descriptive Statistics in R, Statistical Graphics, Basic Hypothesis Testing in R |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BSCSC401 | Computer Science – Database Management Systems | Major Core | 4 | DBMS Architecture, ER Model, Relational Model, SQL Commands, Normalization, Transaction Management |
| BSMAT401 | Mathematics – Ring Theory and Vector Spaces | Major Core | 4 | Rings and Fields, Integral Domains, Ideals and Quotient Rings, Vector Spaces and Subspaces, Linear Transformations, Basis and Dimension |
| BSSTA401 | Statistics – Statistical Quality Control and Reliability | Major Core | 4 | Quality Control Concepts, Control Charts for Variables, Control Charts for Attributes, Acceptance Sampling, Reliability Measures, Life Distributions |
| OE401 | Open Elective (e.g., Financial Management) | Elective | 3 | Financial Markets, Capital Budgeting, Working Capital Management, Sources of Finance, Investment Decisions |
| SEC401 | Skill Enhancement Course (e.g., Python Programming for Data Science) | SEC | 2 | Python Basics, Data Structures in Python, NumPy for Numerical Computing, Pandas for Data Analysis, Data Visualization with Matplotlib, Introduction to Scikit-learn |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BSCSC501 | Computer Science – Operating Systems | Major Core | 4 | Operating System Concepts, Process Management, CPU Scheduling, Deadlocks, Memory Management, File Systems |
| BSMAT501 | Mathematics – Complex Analysis | Major Core | 4 | Complex Numbers and Functions, Analytic Functions, Cauchy-Riemann Equations, Complex Integration, Cauchy''''s Integral Theorem, Residue Theorem |
| BSSTA501 | Statistics – Econometrics and Time Series Analysis | Major Core | 4 | Econometric Models, Linear Regression Models, Multiple Regression Analysis, Assumptions and Violations, Time Series Components, ARIMA Models |
| OE501 | Open Elective (e.g., Entrepreneurship Development) | Elective | 3 | Entrepreneurship Ecosystem, Business Idea Generation, Market Analysis, Business Plan Development, Funding and Legal Aspects |
| VAC501 | Value Added Course (e.g., Communication Skills for Professionals) | VAC | 2 | Verbal Communication, Non-Verbal Communication, Presentation Skills, Interview Techniques, Professional Correspondence |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BSCSC601 | Computer Science – Computer Networks | Major Core | 4 | Network Topologies, OSI and TCP/IP Models, Data Link Layer, Network Layer, Transport Layer, Network Security |
| BSMAT601 | Mathematics – Operations Research | Major Core | 4 | Linear Programming Problems, Simplex Method, Duality in LPP, Transportation Problem, Assignment Problem, Game Theory |
| BSSTA601 | Statistics – Multivariate Analysis and Categorical Data Analysis | Major Core | 4 | Multivariate Normal Distribution, Principal Component Analysis, Factor Analysis, Discriminant Analysis, Logistic Regression, Loglinear Models |
| PROJ601 | Interdisciplinary Project | Project | 6 | Project Planning, Literature Review, Data Collection and Analysis, Report Writing, Presentation Skills, Problem Solving |
| OE601 | Open Elective (e.g., Cyber Security) | Elective | 3 | Cybersecurity Fundamentals, Network Security, Cryptography, Malware Analysis, Ethical Hacking, Cyber Laws |
