Course Description
Through this program, you will learn how to analyze and interpret data, identify patterns and trends, and communicate insights to stakeholders. The program covers key topics, such as data visualization, data cleaning and transformation, statistical analysis, and data modeling. You will also learn how to use different tools and technologies for data analytics, including Excel, SQL, Python, Power BI and Tableau.
Course Objectives:
- Understanding of the mathematical and computational foundations of data analytics
- Comprehensive understanding of statistical foundations for data analytics using Excel, R, and
Python - Analyze and interpret data using advanced Excel and Power Query
- Ability to write Python programs to manipulate and analyze data
- Gain practical experience in working with SQL for data manipulation and analysis.
Learning Outcomes:
After successful completion of this program, a learner will be able to
- Analyze and interpret data to make data-driven decisions
- Apply statistical methods and techniques needed to analyze data and draw meaningful
insight - Extract and analyze data using advanced Excel functions and Power Query
- Apply design principles to enhance the visual appeal of data visualizations
- Create interactive and dynamic visualizations using Power BI and Tableau
- Apply SQL concepts to extract, manipulate, and analyze data.
Conclusion:
This program will teach students how to analyze data, create visualizations, and build dashboards that can help businesses make informed decisions. Upon completion of this course, participants will have the necessary skills to solve real-world problems and effectively communicate their findings to non-technical stakeholders.
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Module 1. Statistical Foundations for Data Analytics
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A) Business Statistics-[15 Hours]
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B) Statistical Analysis Using Excel-[10 Hours]
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C) Statistical Computing Using R Software-[5 Hours]
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D) Statistical Computing Using Python-[5 Hours]
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Module 2. Data Analysis Using Advanced Excel and Power Query-[30 Hours]
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Module 3. Data Visualization Using Excel and Google Data Studio-[10 Hours]
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Module 4. Data Analysis Using R 20 Module-[20 Hours]
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Introduction to Python Programming-[25 Hours]
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Module 1. Inferential Statistics (Using R and Python)-[15 Hours]
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Module 2. Data Analysis Using Python-[20 Hours]
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Module 3. Data Visualization and Storytelling
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A) Principles of Data Visualization -[10 Hours]
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B) Data Visualization Using R-[5 Hours]
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5 C) Data Visualization Using Python-[10 Hours]
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D) Data Visualization and Modelling Using Power BI-[30 Hours]
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E) Data Visualization Using Tableau-[25 Hours]
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Module 4. SQL for Data Analysis (MySQL/Microsoft SQL Server)-[25 Hours]
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Module 5. Case Studies/Mini Projects-[10 Hours]
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Module 6. Interview Preparation
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