(2019 Pattern)
| Subject | Outcomes |
| CS-111 Problem Solving using Computer and ‘C’ Programming | CO1: . Explore algorithmic approaches to problem solving. CO2: Develop modular programs using control structures and arrays in ‘C’. |
| CS-112 Database Management Systems | CO1: Solve real world problems using appropriate set, function, and relational models. CO2: Design E-R Model for given requirements and convert the same into database tables. CO3: Use SQL |
| CS-113 Practical course based on CS101 and CS102 | CO1: Devise pseudocodes and flowchart for computational problems. CO2: Write, debug and execute simple programs in ‘C’. CO3: Create database tables in postgreSQL. CO4: Write and execute simple, nested queries. |
| ELC-111 Semiconductor Devices and Basic Electronic Systems | CO1: To study various types of semiconductor devices. CO2: To study elementary electronic circuits and systems |
| ELC-112 Principles of Digital Electronics | CO1: To get familiar with concepts of digital electronics. CO2: To learn number systems and their representation. CO3: To understand basic logic gates, Boolean algebra and K-maps . CO4: To study arithmetic circuits, combinational circuits and sequential circuits |
| ELC-113 III Electronics Lab IA | CO1: To create foundation for research and development in Electronics/ Computer Science. CO2:To develop analytical abilities towards real world problems. To help students to build-up a progressive and successful career. |
| MTC-111 Matrix Algebra | CO1: To understand the basic components in electronics with their symbol, working principle and classifications. Demonstrate quantitative problem solving skills in all the topics covered. CO2: Understand the basic characteristics and operation of semiconductor devices such as p-n junctions and Zener diodes, LED etc. CO3: Understand the basic concepts of Transistor and its configurations. basic construction, equivalent circuits and characteristics of unipolar devices such as UJT,JFET and MOSFET |
| MTC-112 Discrete Mathematics | CO1: A students should be able to work with graphs and identify certain parameters and properties of the given graphs. CO1: A students should be able to perform certain algorithms, justify why these algorithms work, and give some estimates of the running times of these algorithms |
| MTC-113 Mathematics Practica | CO1: A students should be able to work with graphs and identify certain parameters and properties of the given graphs. CO2: A students should be able to perform certain algorithms, justify why these algorithms work, and give some estimates of the running times of these algorithms. |
| CSST 111 Descriptive Statistics I | CO1: Develop skills in presenting quantitative data using appropriate diagrams, tabulations and summaries and Fundamental statistical measures: Average, median, mode, mean, absolute deviations. CO2: How to calculate and apply measures of location and measures of dispersion — grouped and ungrouped data cases. Use appropriate statistical skewness and kurtosis methods in the analysis of simple datasets. CO3: To give general idea to distinct value of the random variable for each distinct variable and To study Random variables and their distributions:uniform, binomial, Bernoulli, Poisson, geometric Calculate and interprete coefficient of correlation and determination and Bivariate and Multivariate Regression and Correlation. To understand real life situations of time series |
| CSST 112 Mathematical Statistics | CO1: To understand revision of theory of probability and advance theory of probability. CO2: Learn random variables and continuous probability distributions. CO3: Learn about the large and small sample test and non parametric test. |
| CSST113 Statistics Practical Paper I | CO1: To tabulate and make frequency distribution of the given data. CO2: To use various graphical and diagrammatic techniques and interpret. CO3: To compute various measures of central tendency, dispersion, Skewness and kurtosis. CO4: To fit the Binomial and Poisson distributions. CO5: To compute the measures of attributes. CO6: The process of collection of data, its condensation and representation for real life data. CO7: To study free statistical softwares and use them for data analysis in project |
| CS-121 Advanced ‘C’ Programming | CO1: Develop modular programs using control structures, pointers, arrays, strings and structures CO2: Design and develop solutions to real world problems using C |
| CS-122 Relational Database Management Systems | Design E-R Model for given requirements and convert the same into database tables. CO1: Use database techniques such as SQL & PL/SQL. CO2: Explain transaction Management in relational database System. CO3: Use advanced database Programming concepts |
| S-123 Practical course based on CS201 and CS202 | CO1: Write, debug and execute programs using advanced features in ‘C’. CO2: To use SQL & PL/SQL. CO3: To perform advanced database operations |
| ELC-121 Instrumentation System | CO1: To study Instrumentation System. CO2: To study various blocks of Instrumentation System. CO3: To study Smart Instrumentation System |
| ELC-122 Basics of Computer Organisation | CO1: To get familiar digital sequential circuits. CO2: To study Basic computer Organization. CO3: To study Memory architecture |
| ELC-123 Electronics Lab IB | CO1: To help students to build-up a progressive and successful career. CO2: To develop analytical abilities towards real world problems |
| MTC-121 Linear Algebra | CO1: Study of vector. CO2: Orthogonality and Symmetric Matrices. CO3: The Geometry of vector spaces |
| MTC-122 Graph Theory | CO1: Connected graph, tree. CO2: Introduction to graph. |
| MTC-123 Mathematics Practical | CO1: Practical based on the applications of articles in MTC- 121 and MTC- 122 |
| CSST121 Methods of Applied Statistics | CO1: To tabulate and make frequency distribution of the given data. CO2: To use various graphical and diagrammatic techniques and interpret. |
| CSST122 Continuous Probability Distributions and Testing of Hypothesis | CO1: To compute various measures of central tendency, dispersion, Skewness and kurtosis. CO2: To fit the Binomial and Poisson distributions. |
| CSST123 Statistics Practical Paper II | CO1: To understand the relationship between two variables using scatter plot. CO2: To compute coefficient of correlation, coefficient of regression. CO3: To fit various regression models and to find best fit. CO4: To fit the Normal distribution. CO5: To understand the trend in time series and how to remove it. CO6: To apply inferential methods for real data sets. CO7: To generate model sample from given distributions. CO8: To understand the importance and functions of different statistical organizations in the development of nation. |