
Digital Analytics & Regression
Learn how to communicate data-driven results effectively. Get practical experience using Google Trends, R Studio, and other technologies. Discover how to formulate business objectives using data science tools.
Digital Analytics & Regression Highlights
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Duration
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Fee US$ 99 - US$ 199 |
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Duration
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Fee US$ 99 - US$ 199 |
Course Outline
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Once you have completed this course, you will earn your certificate.
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Course details
Certificate
- IBM Certificate
About this course
- 05 Modules
- 04 Skills
Includes
- Discussion space
- 04 Hands-on labs
- 04 Graded quizzes
- 01 Final exam
Exercises to explore
- Importing data sets
- Plotting and correlation
- Linear regression
- Data presentation
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Shingai Manjengwa
- Director, Technical Education
- View on LinkedIn
FAQs
Data science is a blend of programming tools, statistical analysis, algorithms, and machine learning principles that is becoming increasingly popular. It involves the application of a variety of disciplines, including statistics, scientific methodologies, artificial intelligence (AI), and data analysis.
A data analyst is someone who analyses data and develops insightful conclusions from their findings, which then help to clarify a company's market position. Typical responsibilities include:
- Data extraction utilizing high-tech computer models.
- Deleting damaged data, and other related tasks.
- Performing preliminary analysis to determine the quality of the data.
- Preparing presentations based on the data analysis.
- Making presentations to senior management.
Data is an important firm asset, and data-driven business processes improve efficiency and spur innovation. Thus, the demand for data scientists with strong skills is growing, and firms are willing to offer very competitive packages to attract the most qualified individuals. Some well-known data science service providers include:
1. Oracle
2. Amazon
3. JP Morgan Chase
4. Teradata
5. Accenture
Data Analytics & Regression is a self-paced online course. As a result, you will require internet connectivity in order to use the course materials. When you register for this course, you will immediately have access to the course materials through the course link in your dashboard.
This course is completely self-paced.
A self-paced course does not follow a defined schedule for live sessions or webinars. Instead, you can work as swiftly or as slowly as you wish as long as you complete the modules and the course before the end of your enrollment.
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