Data Analytics and Machine Learning

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Data Analytics and Machine Learning

Data analytics and machine learning are foundational components of modern data-driven decision-making processes. This course offers a comprehensive exploration of both disciplines, equipping students with the knowledge and skills necessary to extract valuable insights from data and build predictive models. Through a combination of theoretical lectures, practical exercises, and hands-on projects, participants will learn how to leverage various data analytics techniques and machine learning algorithms to analyze data, make informed decisions, and solve complex problems across different domains

Course Objectives

  • Understand the fundamental concepts and principles of data analytics and machine learning.
  • Learn how to collect, preprocess, and explore data using descriptive analytics techniques.
  • Gain proficiency in data visualization and interpretation to communicate insights effectively.
  • Explore various machine learning algorithms for supervised, unsupervised, and reinforcement learning tasks.
  • Understand the process of model training, evaluation, and deployment in machine learning pipelines.
  • Develop practical skills in building predictive models and conducting feature engineering.
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