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Module 1. Fundamentals of Data Science -[5 Hours]
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Module 2. Statistical Foundations for Data Science
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A) Descriptive Statistics -[15 Hours]
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B) Probability and Probability Distributions -[15 Hours]
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C) Statistical Computing Using R Software -[10 Hours]
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D) Statistical Computing Using Python -[10 Hours]
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Module 3. Data Science Using R-[40 Hours]
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Module 4. Python for Data Science -[40 Hours]
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Module 5. Data Analysis Using Advanced Excel and Power Query -[25 Hours]
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Module 6. Data Visualization Using Excel and Google Data Studio (Self-paced Learning)
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Module 1. Inferential Statistics (Using R and Python) -[20 Hours]
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Module 2. Data Science Using Python -[20 Hours]
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Module 3. Machine Learning (Using Python and R) -[60 Hours]
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Module 4. Matrix Algebra (Using Python) -[5 Hours]
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Module 5. Pre-Calculus (Using Python) -[10 Hours]
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Module 6. SQL for Data Science (MySQL/Microsoft SQL Server) -[30 Hours]
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Module 7. 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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C) Data Visualization Using Python-[10 Hours]
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E) Data Visualization Using Tableau-[30 Hours]
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E) Data Visualization Using Tableau -[25 Hours]
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Module 9. Interview Preparation -[30 Hours]
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Module 1. Fundamentals of Data Science -[5 Hours]
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Module 2. Computational Thinking and Programming Fundamentals -[5 Hours]
Module 2. Computational Thinking and Programming Fundamentals -[5 Hours]
Module 2. Statistical Foundations for Data Science
Module 2. Statistical Foundations for Data Science