- Instructor: teamsource_traning_control
- Lectures: 50
- Quizzes: 3
- Duration: 10 weeks
Categories: Data
“Turn raw data into powerful insights that drive real business results!”
This course teaches you how to collect, clean, and analyze data effectively using industry-standard tools. You’ll master data visualization, reporting, and interpretation techniques that help make smarter decisions. By the end, you’ll be able to transform complex datasets into actionable insights, build dashboards, and communicate findings clearly to stakeholders — skills highly sought after in finance, marketing, and business analytics roles.
Curriculum
- 9 Sections
- 50 Lessons
- 10 Weeks
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- Introduction to Data AnalyticsThis section introduces students to the field of data analytics, highlighting its importance in decision-making across industries. Students will learn the roles of a data analyst, key concepts in data handling, and the tools commonly used for data analysis.6
- Data Collection and CleaningAccurate analysis starts with high-quality data. This section teaches students how to collect, clean, and prepare data for analysis, ensuring results are reliable and actionable.6
- Data Exploration and VisualizationStudents will learn how to explore data, identify trends, and present insights visually. This section focuses on understanding patterns and communicating results effectively.6
- Statistical Analysis for DataThis section introduces essential statistical concepts that help analysts make data-driven decisions. Students will learn to summarize, analyze, and interpret data quantitatively.6
- Introduction to SQL and DatabasesData is often stored in databases. Students will learn SQL fundamentals to query and manipulate data efficiently, an essential skill for any data analyst.6
- Advanced Analytics ToolsStudents explore advanced tools for analyzing large datasets, including Python, R, and other analytics platforms. This section teaches students how to automate analysis and gain deeper insights from data.6
- Predictive Analytics and Machine Learning BasicsThis section introduces students to predictive modeling and machine learning, showing how analytics can forecast trends and support decision-making.6
- Data Analytics Best PracticesStudents will learn industry best practices for working with data, ensuring accuracy, reproducibility, and compliance with ethical and privacy standards.5
- Capstone Project – Real-World Data AnalysisIn the final section, students apply all skills to a real-world dataset. They will clean, analyze, visualize, and present their findings, simulating a professional analytics project.6
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