Description:

This course covers the fundamentals of data science with a focus on the year 2023. It provides an in-depth understanding of key concepts, techniques, and tools used in data science. Students will learn how to collect, analyze, and interpret large datasets to extract valuable insights and make data-driven decisions. The course also introduces advanced topics such as machine learning, deep learning, and predictive analytics, empowering students to solve complex real-world problems using data science methodologies.

Key Highlights:

• Comprehensive coverage of data science principles and techniques
• Hands-on experience with data analysis and visualization tools
• Introduction to machine learning and predictive analytics
• Real-world projects and case studies
• Expert guidance from experienced instructors

What you will learn:

• Learning Outcome 1
  Gain a solid foundation of data science principles, including data preprocessing, exploratory data analysis, and statistical modeling.
• Learning Outcome 2
  Develop proficiency in popular data analysis and visualization tools like Python, R, and Tableau to extract actionable insights from datasets.
• Learning Outcome 3
  Understand and apply machine learning algorithms, including regression, classification, clustering, and dimensionality reduction.
• Learning Outcome 4
  Explore advanced topics such as deep learning, natural language processing, and reinforcement learning to solve complex data science problems.
• Learning Outcome 5
  Apply data science techniques to real-world projects and case studies, gaining hands-on experience in solving practical data-driven challenges.