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.
Read More🔧 Master Embedded Systems with AVR Microcontroller! 🔧
Take Control of Technology – One Byte at a Time 🚀 Course Title: Embedded System with AVR Microcontroller 📅 Duration: …
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