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In today’s data-driven world, the ability to analyze, interpret, and act on data is not just valuable—it’s essential. INF-202: Data Analytics offers students a comprehensive introduction to the field of data analytics, empowering them with the tools and techniques needed to uncover actionable insights from raw data. Whether you're a future business analyst, software developer, researcher, or simply data-curious, this course lays the groundwork for informed, evidence-based decision-making across industries.
Course Overview INF-202 explores the full data analytics lifecycle, from data collection and cleaning to visualization and interpretation. Students gain practical, hands-on experience with industry-standard tools such as Microsoft Excel, SQL, and Python. The course also introduces essential statistical concepts and data modeling techniques used in real-world applications, preparing students to analyze both structured and unstructured datasets.
Key Topics Include:
Introduction to Data Analytics and Its Applications Data Types, Sources, and Collection Methods Data Cleaning and Preprocessing Techniques Exploratory Data Analysis (EDA) Descriptive and Inferential Statistics Data Visualization with Tools like Tableau and Matplotlib Basics of Machine Learning Models in Analytics Ethical Use of Data and Privacy Considerations
Through interactive lectures, real-world case studies, and group projects, INF-202 ensures students not only understand theoretical concepts but also know how to apply them in professional settings.
Why Take INF-202? Data is the new oil—and those who know how to refine it are in high demand. INF-202 gives students the edge in a competitive job market by building both technical and analytical thinking skills. Graduates of this course often pursue careers in data analysis, business intelligence, marketing analytics, and IT consulting. Others continue with advanced study in data science, artificial intelligence, or economics.
The course emphasizes not just "how" to analyze data, but also "why" it matters. By the end of INF-202, students will be able to frame analytical problems, select appropriate tools and methods, and communicate insights clearly to stakeholders.
Course Format and Assessment INF-202 Data Analytics combines theory with practice in a structured learning environment. Weekly labs allow students to apply concepts immediately, while assessments include quizzes, data projects, and a capstone assignment involving a full-cycle analysis of a real dataset. Peer collaboration and instructor feedback foster an interactive and engaging learning experience.
Prerequisites: Basic knowledge of mathematics and introductory programming is recommended but not required. INF-202 is designed to be accessible to students from diverse academic backgrounds.
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