Digital Analytics & Regression
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Course
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.
Self-Paced
Mentored
Beginner
Duration
2-4 hours/week
Digital analytics helps organizations provide a better online experience to their clients and potential customers. Within this, regression analysis helps businesses understand the data points they have and enables them to improve their decision making.
During this course, you will work on a case study - CEO vs CMO - to decide upon an appropriate name for a new cloud-based technology. During this exercise, youll build your understanding of the business context, formulate the business objective, state the hypothesis, assess available data, and assign data for use. You will also learn about the R programming language and its suitability for data analysis, including how to load data into R-Studio and view the rows in the resulting dataset.
Additionally, you will access Google trends - a web tool - in R and analyze various Google search trends. You will also discover how to access Google Trends on R Studio, and view the output in the form of box plots, histograms, scatter plots and linear regression trends. In the final module, you will then summarize the data analytics process and focus on the conclusions and recommendations you would make to the relevant stakeholders.
Once you have completed this course, you will be able to define business objectives from big, medium or small data using data science tools and Google Trends. For individuals keen to learn how to communicate data-driven results to the relevant stakeholders, this course is an ideal place to start.
This course comprises five purposely designed modules that take you on a carefully defined learning journey.
It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes to complete, it is anticipated that if you work 2-4 hours per week, you will complete the course in 4 weeks. However, as long as the course is completed by the end of your enrollment, you can work at your own pace. And dont worry, youre not alone! You will be encouraged to stay connected with your learning community and mentors through the course discussion space.
The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include discussion space, videos, reading material, quizzes, hands-on labs, quizzes and a final assignment.
Once you have successfully completed the course, you will earn your IBM Certificate.
As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. Depending on the payment plan you have chosen, you may also have access to live classes and webinars, which are an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services may vary package wise.
You will understand:
- The business analytics cycle.
- How to create a analytics solution.
- How to articulate a recommendation.
There are no prerequisites for this course, however, knowledge of basic statistics and basic R is beneficial.