GRADUDATA- DATA SCIENCE / DATA ANALYTICS Courses

Integrated Learning Program in Data Science, Machine Learning and Artificial Intelligence

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    • Module 1. Mathematical Pre-requisite for Data Science[15 Hours]
    • Module 2. Computational Thinking and Programming Fundamentals[5 Hours]
    • Module 1. Fundamentals of Data Science[5 Hours]
    • Module 2. Statistical Foundations for Data Science
    • A) Descriptive Statistics[15 Hours]
    • B) Probability and Probability Distributions[15 Hours]
    • C) Statistical Computing Using R Software[10 Hours]
    • D) Statistical Computing Using Python[10 Hours]
    • Module 3. Data Science Using R[40 Hours]
    • Module 4. Python for Data Science[40 Hours]
    • Module 5. Data Analysis Using Advanced Excel and Power Query[25 Hours]
    • Module 6. Data Visualization Using Excel and Google Data Studio (Self-paced Learning)
    • Module 1. Inferential Statistics (Using R and Python)[20 Hours]
    • Module 2. Data Science Using Python[25 Hours]
    • Module 3. Machine Learning (Using Python and R)[60 Hours]
    • Module 4. Matrix Algebra (Using Python)[5 Hours]
    • Module 5. Pre-Calculus (Using Python)[10 Hours]
    • Module 6. SQL for Data Science (MySQL/Microsoft SQL Server)[30 Hours]
    • Module 7. Data Visualization and Storytelling[10 Hours]
    • A) Principles of Data Visualization[10 Hours]
    • B) Data Visualization Using R[5 Hours]
    • C) Data Visualization Using Python[10 Hours]
    • D) Data Visualization and Modelling Using Power BI[30 Hours]
    • E) Data Visualization Using Tableau[25Hours]
    • Module 8. Case Studies/Mini Projects[30 Hours]
    • Module 9. Interview Preparation
    • Module 1. Linear Algebra (Using Python)[15]
    • Module 2. Multivariate Calculus and Optimization Techniques (Using Python)[15 Hours]
    • Module 3. Advanced Topics in Machine Learning (Using Python)[20 Hours]
    • Module 4. Deep Learning and Computer Vision (Using Python)[50 Hours]
    • Module 5. Natural Language Processing (Using Python)[20 Hours]
    • Module 6. Time Series Analysis and Business Forecasting (Using Python)[ 15 Hours]
    • Module 7. Model Deployment[10 Hours]
    • Module 8. Case Studies/Mini Projects[30 Hours]
    • Module 9. Research Papers Reading[5 Hours]
    • Module 9. Research Papers Reading
    • Module 10. Web Scrapping (Self-paced Learning)
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Module 6. Time Series Analysis and Business Forecasting (Using Python)[ 15 Hours]
Module 6. Time Series Analysis and Business Forecasting (Using Python)[ 15 Hours]
Module 8. Case Studies/Mini Projects[30 Hours]
Module 8. Case Studies/Mini Projects[30 Hours]
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We believe that these combinations sets us apart from other institutes and makes us the ideal choice for students looking to advance their careers in the fields of Data Science, Machine Learning, and Analytics. Thank you for considering GraduDATA as your training provider.

  • Data Science, Machine Learning and Artificial Intelligence
  • Data Science and Machine Learning
  • Data Analytics/ Business Analytics
  • Business Intelligence
  • Data Visualization and Storytelling
  • Data Science and Machine Learning
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