Data Science & Analytics
This course explores the complete data science lifecycle, from data acquisition and preparation to analysis, visualization, and predictive analytics. Participants will learn how organizations use data to solve business problems, improve operations, and gain competitive advantages.
Learning Outcomes
Participants will be able to:
• Understand the fundamentals of Data Science and Analytics
• Collect, clean, and prepare datasets for analysis
• Perform exploratory data analysis (EDA)
• Apply statistical techniques to solve business problems
• Create compelling data visualizations and dashboards
• Use Python and analytical tools for data analysis
• Build predictive models using machine learning techniques
• Communicate insights through reports and presentations
Basic computer literacy
• Familiarity with Microsoft Excel or spreadsheets
• Basic mathematical understanding
• Interest in data analysis and problem-solving
• Access to a computer with internet connectivity
Aspiring Data Scientists
• Data Analysts
• Business Analysts
• Software Developers
• AI and Machine Learning Enthusiasts
• Researchers and Academics
• Entrepreneurs and Decision Makers
• Students pursuing technology careers
- Description
- Curriculum
- Notice
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This course provides a comprehensive introduction to Data Science and Analytics. Participants will learn how to collect, process, analyze, and visualize data to uncover valuable insights and support business decision-making. Through practical projects and real-world case studies, learners will develop skills in data analysis, business intelligence, statistical methods, and predictive modeling.
Basic computer literacy is required. Familiarity with spreadsheets and basic mathematics is beneficial but not mandatory. Participants will gain hands-on experience working with real-world datasets, data visualization tools, and analytical techniques used across industries.
