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Data Analytics

Data Analytics Course Learn the fundamentals of data analysis, including data collection, cleaning, visualization, and interpretation. This course covers ess...

Course Overview

Data Analytics Course

This comprehensive course is designed to equip you with the essential skills needed to analyze and interpret data effectively. You will learn how to collect, clean, and visualize data, uncover trends, and make data-driven decisions using industry-standard tools.

What You’ll Learn:

✅ Data Fundamentals – Understanding data types, sources, and collection methods.
✅ Data Cleaning & Processing – Handling missing data, filtering, and transforming datasets.
✅ Data Visualization – Creating meaningful charts and dashboards using Excel, SQL, and Python.
✅ Statistical Analysis – Applying key statistical techniques to interpret trends.
✅ Business Intelligence – Using data to make informed business decisions.
✅ Real-World Projects – Hands-on exercises to apply your knowledge in real scenarios.

By the end of this course, you will have the skills to analyze data confidently, create compelling reports, and support decision-making in any industry. Whether you’re a beginner or looking to enhance your career, this course will prepare you for success in the data-driven world.

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Course curriculum

Requirment

1. Must have a reliable high-speed Internet connection
2. Must own a computer (desktop or laptop) that meets minimum hardware specifications
3. Must use an up-to-date web browser and operating system
4. Must have a quiet, dedicated study space
5. Must have a functioning webcam and microphone
6. Must be comfortable using basic digital tools (e.g., email, word processors, spreadsheets)
7. Must have a proactive time management plan
8. Must ensure access to required digital platforms (LMS, cloud storage, analytics portals)
9. Must commit to regular attendance (synchronous sessions or scheduled self-study sessions)
10. Must be prepared to work both independently and in collaborative settings
11. Must be open to exploring real-world datasets and case studies
12. Must actively engage with instructor feedback and peer reviews

Outcomes

Students will consistently access online datasets, digital tools, and cloud-based analytics platforms without interruption.
Students will smoothly run data analytics software and process large datasets without technical delays.
Students will have seamless access to course resources, virtual labs, and online collaboration platforms.
Students will concentrate during virtual sessions and complete assignments efficiently in a distraction-free environment.
Students will actively participate in live lectures, group discussions, and virtual project meetings.
Students will navigate the Learning Management System (LMS) and utilize digital resources to submit assignments and collaborate with peers effectively.
Students will meet project deadlines and manage their study schedule, ensuring timely completion of assignments and active engagement throughout the course.
Students will reliably use these platforms to submit work, retrieve course materials, and collaborate on group assignments without technical interruptions.
Students will actively participate in all scheduled sessions, reinforcing their understanding of data analysis methods and enhancing overall course engagement.
Students will demonstrate strong analytical skills by independently analyzing data and effectively collaborating in team projects to interpret complex datasets.
Students will apply analytical methods to extract insights from actual datasets, supporting their ability to solve practical business and research problems.
Students will refine their data analysis approaches, resulting in progressively improved projects and clearer communication of analytical findings in written reports.