Data ScienceSemester 2-2 syllabus

This semester layers statistical and data-engineering foundations onto the programming base built earlier, introducing DBMS, computer organization, and a dedicated data-engineering track alongside its lab. A design-thinking course and an optimization-techniques course broaden the student’s problem-solving toolkit, and the term closes with a mandatory eight-week community-service internship over the summer break.

Semester load: roughly 15 lecture, 1 tutorial and 10 practical hours per week, totaling 21 credits.

Subjects

Optimization Techniques

• Unit 1: Formulating optimization problems and classical unconstrained/constrained techniques (Lagrange multipliers, Kuhn-Tucker)
• Unit 2: Linear programming and the simplex method
• Unit 3: Transportation problems and feasibility methods
• Unit 4: Nonlinear programming, one-dimensional search methods, and penalty-function approaches
• Unit 5: Dynamic programming and multistage decision processes

Statistical Methods for Data Science

• Unit 1: Exploratory data visualization techniques and common probability distributions
• Unit 2: Parametric estimation and hypothesis testing
• Unit 3: Linear and multiple regression, including categorical predictors
• Unit 4: Time-series analysis — trend, seasonality, and smoothing methods
• Unit 5: Logistic regression for classification problems

Data Engineering

• Unit 1: What data engineering involves and how the role differs from data science
• Unit 2: The data engineering life cycle — generation, storage, ingestion, transformation, and serving
• Unit 3: Principles of sound data architecture and how source systems generate data
• Unit 4: Storage systems (warehouses, lakes, lakehouses) and ingestion strategies
• Unit 5: Query optimization, data modeling, and streaming transformations

Database Management Systems

• Unit 1: Database fundamentals, schema architecture, and entity-relationship modeling
• Unit 2: The relational model, relational algebra, and basic SQL
• Unit 3: Intermediate SQL — joins, subqueries, grouping, and views
• Unit 4: Normalization theory from first through fifth normal form
• Unit 5: Transaction management, concurrency control, recovery, and indexing structures

Computer Organization and Architecture

• Unit 1: Number systems, data representation, and Boolean logic minimization
• Unit 2: Combinational and sequential digital circuits
• Unit 3: Computer arithmetic, register-transfer operations, and the stored-program model
• Unit 4: Microprogrammed control and CPU instruction/addressing design
• Unit 5: Memory hierarchy and input-output organization

Data Engineering Lab

• Setting up pipeline tooling such as Apache NiFi, Airflow, Elasticsearch, and PostgreSQL
• Reading, writing, and transforming data across files and databases
• Building, versioning, and monitoring data pipelines
• Deploying a pipeline into a production-like environment
• Total: 3 practical hours per week, 1.5 credits

DBMS Lab

• DDL/DML/DCL exercises, nested queries, and aggregate functions
• PL/SQL programming — control structures, procedures, functions, cursors, and triggers
• Indexing exercises and JDBC-based database connectivity from Java
• Total: 3 practical hours per week, 1.5 credits

Exploratory Data Analysis with Python (Skill Enhancement Course)

• Unit 1: EDA fundamentals and getting comfortable with common Python libraries
• Unit 2: Visual analysis techniques — line, bar, scatter, and other chart types
• Unit 3: Data transformation — merging, reshaping, and handling missing values
• Unit 4: Descriptive statistics, distribution types, and correlation analysis
• Unit 5: A basic model-development and evaluation workflow
• Total: 1 tutorial and 2 practical hours per week, 2 credits

Design Thinking & Innovation

• Unit 1: Elements and principles of design, and the history of design thinking
• Unit 2: The design thinking process — empathize, analyze, ideate, and prototype
• Unit 3: Innovation versus creativity, and building teams around innovation
• Unit 4: Product design strategy, specification, and planning
• Unit 5: Applying design thinking to business strategy and startups

Note: this semester is paired with a mandatory eight-week Community Service Project Internship during the summer vacation.