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Categories: Business Marketing Math

About Course

Introduction to Data Analysis is a foundational course aimed at teaching students essential skills for understanding and interpreting data and also how to monetize these skills on various crowdsourcing platforms. The course covers:

  • Data Collection and Cleaning: Techniques for gathering and preparing data, including handling missing values and inconsistencies.
  • Descriptive Statistics: Methods for summarizing and visualizing data, such as using mean, median, and standard deviation, along with visual tools like histograms and scatter plots.
  • Inferential Statistics: Basics of hypothesis testing, confidence intervals, and regression analysis to draw conclusions about populations from sample data.
  • Data Visualization: Skills for analyzing results and recognizing data limitations and biases.
  • Practical Applications: Application of data analysis techniques to real-world problems through case studies and exercises.
  • Skill monetization: Step-by-step guide on the opening of relevant online work platforms for data analysis skills monetization.

By the end of the course, students will be equipped to effectively analyze data and make informed decisions based on their findings.

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Course Content

Module 1: Introduction to Data Analytics and Spreadsheet
This course provides a foundational understanding of data analytics concepts and practical skills in using spreadsheet software for data analysis. Students will learn how to collect, organize, analyze, and visualize data to support decision-making processes in various contexts. Course Objectives: Understand the fundamental principles of data analytics. Gain proficiency in spreadsheet tools, focusing on Excel or Google Sheets. Learn data manipulation techniques, including sorting, filtering, and using formulas. Develop skills in data visualization to communicate insights effectively. Explore basic statistical concepts relevant to data analysis.

  • Introduction to Data Analytics
    00:00
  • Spreadsheet Fundamentals
    00:00
  • Data Manipulation Techniques
    00:00
  • Practice Quiz

Module 2: Data collection and Data cleansing techniques
This course focuses on the essential processes of data collection and data cleansing, crucial steps in ensuring high-quality data for analysis. Students will learn various methodologies for gathering data from multiple sources and techniques for cleaning and preparing data for further analysis. Course Objectives: Understand the importance of data collection and cleansing in the data analytics process. Learn various data collection methods and tools. Gain skills in identifying and addressing data quality issues. Explore techniques for transforming and preparing data for analysis.

Module 3: Data Analysis using statistical methods
This course introduces fundamental statistical concepts and techniques that are essential for analyzing and interpreting data. Students will learn the principles of descriptive and inferential statistics, enabling them to make informed decisions based on data insights. Course Objectives: Understand key statistical concepts and terminology. Apply descriptive statistics to summarize data effectively. Conduct basic inferential statistics to draw conclusions from sample data. Interpret and communicate statistical results in a clear manner.

Module 4: Data visuaization and dashboarding using excel
This course offers a comprehensive introduction to data visualization and dashboard creation using Microsoft Excel. Students will learn how to transform raw data into insightful visual representations and interactive dashboards that facilitate data-driven decision-making. Course Objectives: Understand the principles of effective data visualization. Gain proficiency in using Excel’s visualization tools and features. Create interactive dashboards that summarize and display key metrics. Develop skills to communicate insights effectively through visual means.

Module 5: Introduction to power Bi
his course provides an overview of Power BI, a powerful business analytics tool by Microsoft. Students will learn how to connect to various data sources, create interactive reports, and share insights through dashboards. The course emphasizes practical application, enabling learners to leverage Power BI for effective data visualization and decision-making. Course Objectives: Understand the Power BI ecosystem and its components. Connect to various data sources and import data into Power BI

Module 6: Dashboarding and Storytelling in Power Bi
This course delves into the art and science of creating impactful dashboards and compelling narratives using Power BI. Students will learn how to design interactive dashboards that effectively communicate insights and drive decision-making. The course emphasizes storytelling techniques that enhance data presentation and engagement. Course Objectives: Understand the principles of effective dashboard design. Create interactive dashboards that facilitate data exploration and insights. Utilize storytelling techniques to present data narratives effectively. Develop skills to communicate complex data insights clearly and persuasively.

Module 7: Online Work Platforms for Data Analysts
This course provides an overview of various online work platforms and tools specifically designed for data analysts. Students will explore the features, functionalities, and best practices of these platforms, enabling them to enhance their productivity, collaboration, and data management skills in a remote work environment. Course Objectives: Understand the role of online work platforms in data analysis and collaboration. Explore popular tools for data visualization, data management, and project management. Learn how to effectively collaborate with teams using online platforms. Develop skills to integrate various tools for a seamless data analysis workflow.

Module 9: Final Exam

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