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About Course

This Data Science & Analytics course is designed to equip you with the skills and knowledge required to analyze complex data and derive actionable insights. You’ll learn how to collect and clean data, perform exploratory data analysis, build machine learning models, and visualize your findings. This hands-on course covers popular tools such as Python, R, SQL, and data visualization platforms like Tableau. Whether you’re new to the field or looking to upgrade your skills, this course provides a comprehensive foundation in data science and analytics. By the end of the course, you’ll be able to apply data-driven decision-making in real-world scenarios and be well-prepared for roles in data science and analytics.

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What Will You Learn?

  • Collect, clean, and analyze data using Python, R, and SQL.
  • Implement machine learning algorithms for predictive analytics.
  • Visualize data insights using Tableau and Python libraries.
  • Understand and apply data science principles in real-world scenarios.
  • Plus, gain experience with big data technologies and cloud-based analytics platforms.

Course Content

Introduction to Data Science and Analytics
10 Lectures . 16h:03min

  • Introduction to Data Science and Analytics
    10:54
  • Data Collection and Cleaning
    05:09
  • Python for Data Science
  • R for Statistical Analysis
  • SQL for Data Manipulation
  • Machine Learning Fundamentals
  • Data Visualization Techniques
  • Predictive Analytics and Model Evaluation
  • Big Data and Cloud Analytics
  • Final Project: End-to-End Data Science Workflow
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4.50
(6 Ratings)
34 Students
8 Courses

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Requirements

  • Basic understanding of Python programming.
  • A computer with internet access.
  • Willingness to learn and apply AI techniques.

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Audience

  • Beginners looking to start a career in AI and machine learning.
  • Data scientists and analysts aiming to upskill in AI.
  • Developers wanting to transition into AI-focused roles.
  • Anyone interested in applying AI to solve real-world problems.