Description:

This course provides a comprehensive introduction to the field of data science. It covers the fundamental concepts, techniques, and tools used in collecting, analyzing, and interpreting large and complex datasets to extract valuable insights and make data-driven decisions. The course combines theoretical concepts with hands-on exercises to give students a practical understanding of data science methodologies and their application in various industries.

Key Highlights:

• Introduction to data science
• Data collection and preprocessing
• Exploratory data analysis
• Statistical modeling and inference
• Machine learning algorithms
• Data visualization
• Big data analytics
• Ethical considerations in data science

What you will learn:

• Learning Outcome 1
  Acquire a solid foundation in the principles and concepts of data science.
• Learning Outcome 2
  Learn various data collection techniques and how to preprocess and clean data for analysis.
• Learning Outcome 3
  Master exploratory data analysis techniques to gain insights and identify patterns in data.
• Learning Outcome 4
  Understand statistical modeling and inference methods for making data-driven decisions.
• Learning Outcome 5
  Explore a wide range of machine learning algorithms and their applications in data science.
• Learning Outcome 6
  Develop skills in data visualization to effectively communicate insights and findings.
• Learning Outcome 7
  Learn techniques for analyzing and interpreting big data to extract meaningful information.
• Learning Outcome 8
  Understand the ethical considerations and challenges in data science, including privacy and bias.