Data Science Course Description Course Title: Data Science Certification Program Course Duration: 12 months (approx. 300 hours) Course Overview: The Data Science Certification Program is designed to equip students with the skills and knowledge required to extract insights from data and drive informed decision-making in various industries. This comprehensive program covers the fundamentals of data science, including data preparation, visualization, machine learning, and statistical modeling. Course Objectives: Upon completing this course, students will be able to: 1. Collect, process, and analyze large datasets to extract meaningful insights. 2. Apply statistical and machine learning techniques to solve real-world problems. 3. Visualize data to communicate findings effectively to stakeholders. 4. Design and implement data-driven solutions to drive business growth. 5. Work with various data science tools and technologies, including Python, R, SQL, and Tableau.
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| Expiry period | Lifetime | ||
| Made in | English | ||
| Last updated at | Wed Dec 2025 | ||
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| Total lectures | 20 | ||
| Total quizzes | 1 | ||
| Total duration | 02:35:43 Hours | ||
| Total enrolment |
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| Number of reviews | 0 | ||
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| Short description | Data Science Course Description Course Title: Data Science Certification Program Course Duration: 12 months (approx. 300 hours) Course Overview: The Data Science Certification Program is designed to equip students with the skills and knowledge required to extract insights from data and drive informed decision-making in various industries. This comprehensive program covers the fundamentals of data science, including data preparation, visualization, machine learning, and statistical modeling. Course Objectives: Upon completing this course, students will be able to: 1. Collect, process, and analyze large datasets to extract meaningful insights. 2. Apply statistical and machine learning techniques to solve real-world problems. 3. Visualize data to communicate findings effectively to stakeholders. 4. Design and implement data-driven solutions to drive business growth. 5. Work with various data science tools and technologies, including Python, R, SQL, and Tableau. | ||
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