Data Stucture & Algorithm
DSA (Data Structures and Algorithms) is the study of organizing data efficiently using data structures like arrays, stacks, and trees, paired with step-by-step procedures (or algorithms) to solve problems effectively. Data structures manage how data is stored and accessed, while algorithms focus on processing this data. Why to Learn DSA? Learning DSA boosts your problem-solving abilities and make you a stronger programmer. DSA is foundation for almost every software like GPS, Search Engines, AI ChatBots, Gaming Apps, Databases, Web Applications, etc Top Companies like Google, Microsoft, Amazon, Apple, Meta and many other heavily focus on DSA in interviews.
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Object Oriented Programming Using Java – I
Java is a high-level, object-oriented programming language developed by Sun Microsystems in 1995. It is platform-independent, which means we can write code once and run it anywhere using the Java Virtual Machine (JVM). Java is mostly used for building desktop applications, web applications, Android apps, and enterprise systems.
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Data Science
Prerequisites Problem solving using computers Basic mathematics and statistics Knowledge of Databases Course Objectives Provide students with knowledge and skills for data-intensive problem solving and scientific discovery Be prepared with a varied range of expertise in different aspects of data science such as data collection, visualization, processing and modeling of large data sets. Acquire good understanding of both the theory and application of applied statistics and computer science based existing data science models to analyze huge data sets originating from diversified application areas. Be better trained professionals to cater the growing demand for data scientists in industry. Course Outcomes On completion of the course, student will be able to– Perform Exploratory Data Analysis Obtain, clean/process, and transform data. Detect and diagnose common data issues, such as missing values, special values, outliers, inconsistencies, and localization. Demonstrate proficiency with statistical analysis of data. Present results using data visualization techniques. Prepare data for use with a variety of statistical methods and models and recognize how the quality of the data and the means of data collection may affect conclusions.
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C Programming
C is a powerful, general-purpose programming language developed by Dennis Ritchie in 1972 at Bell Labs. It is widely used for system and application software development. Known for its efficiency, speed, and close-to-hardware capabilities, C is the foundation for many modern programming languages like C++, Java, and Python. It supports structured programming, uses low-level memory access, and is commonly used in operating systems, embedded systems, and software drivers.
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