Our Data Analytics Foundation course build a foundation level understanding of the concepts relating to generating a research question, collecting, cleaning, and organizing data. The statistical methods, data mining techniques, and algorithms explained in this certification course help learners interpret data and generate insights for their organization by illustrating the findings in plots and graphs to present each business case with solidly backed insights.
Data analytics entails storing structured and unstructured data and transforming data by cleaning it. Data analytics also includes aggregating data and drawing insights from it. However, it is not only for specialists. Most business-oriented roles include requesting or creating reports. Subsequently, it is crucial to understand the basic principles of how data is turned into insights for anyone who is systematically processing information or wants to submit efficient requests for reports to inform the decision-making process.
The EXIN Data Analytics Foundation certification helps professionals understand the basic concepts of data analytics, the activities in the data analysis process, and the different methods used to analyze data. Candidates who pass the exam also know how outputs from the analysis process can be visualized in charts, graphs, and plots.
Includes quizzes, student materials and an official trial exam – No additional resources are required – everything that you need to understand the topics of the DA course is included. The official exam is also provided in the price of this course.
The Data Analytics Foundation certification course validates a candidate’s knowledge on:
• Turning Data into Insights: Understand the fundamental concepts of data analytics, learn how to outline the process of data analysis, and grasp the risks involved in data analytics. • Collecting, Organizing, and Managing Data: Learn how to collect and source public data, manage compliance with data laws, and understand the importance of different types of data. You’ll also explore the utility of distributed file systems and the advantages of cloud solutions. • Cleaning Data: Discover the methods and techniques for data scrubbing and understand the key considerations for data retention. • Analyzing Data: Distinguish between descriptive and inferential statistics, delve into data mining and machine learning, including natural language processing (NLP), and learn how to utilize various data algorithms. • Visualizing Data: Get hands-on with data visualization techniques, explore different types of charts, plots, and heatmaps, and appreciate the role of aesthetic design in data visualization.
There are no mandatory prerequisites.
Exam Information
Number of questions: 40 Multiple-choice questions Pass mark: 65% Duration: 60 minutes Closed book
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