IT Specialist Data Analytics (INF-202)

Categories: Pearson IT SpecialistPearson Skilling Suite

This instructor-led IT Specialist Data Analytics course provides a gentle introduction to the responsible collection and reporting of data, the concepts of data manipulation, data analytics, prediction from data, and data visualization. It aims to provide learners with an understanding of the fundamentals of data and to equip them with the skills necessary to manipulate, analyze, and visualize data using various information and communications technology tools.

Upon completing this course, learners should be able to explain basic statistical terminology and data analytics concepts, manipulate simple data sets, make simple predictions from data, and explain insights from data using meaningful and appealing visualization. Overall, this course covers the entire data analysis process, from understanding the basic principles to reporting the results of data analysis. Knowledge and skills are assessed through case studies, lab assignments, and quizzes.

Learning Outcomes:

Explain the basics of data
Manipulate data
Analyze data
Create and use visualization from data to explain insights
Explain data privacy laws and best practices for responsible data handling

Optional Add-On Exam Voucher

Lesson 1: Data Basics

Define the concept of data: data vs. information; statistics and its relation to data
Describe basic data variable types, including type checking
Describe basic structures used in data analytics: tables, arrays, lists
Describe data categories: structured vs. unstructured data

Lesson 2: Data Manipulation

Import, store, and export data: ETL processing with relational data, delimited files, XML, and JSON
Clean data: common cleaning practices, truncation, data validation
Organize data: sorting, filtering, appending/slicing, pivoting, transposition
Aggregate data: aggregation functions (COUNT, SUM, MIN, MAX, AVG) and GROUP BY/HAVING in SQL

Lesson 3: Data Analysis

Differentiate between types of data analysis: descriptive, diagnostic, predictive, prescriptive analysis; hypothesis testing
Differentiate between data aggregation and interpretation metrics
Differentiate between exploratory data analysis methods: finding relationships, identifying outliers, drilling and mining a dataset
Evaluate and explain results of data analyses, including simple linear regression
Describe the role of artificial intelligence, machine learning, and deep learning in data analysis

Lesson 4: Data Visualization and Communication

Report data using tables and charts; disaggregate data
Create visualizations comparing categories of data (column, bar charts)
Create visualizations showing parts of a whole (pie, donut, stacked bar/column charts)
Create visualizations analyzing trends (line chart, waterfall chart, Sankey diagram)
Create visualizations showing data distribution (box and whisker plot)
Create visualizations analyzing relationships between sets of values (scatter plot, bubble chart)

Lesson 5: Responsible Analytics Practice

Describe data privacy laws and best practices, including fair information practice principles and privacy laws in the US, Canada, and EU
Describe best practices for responsible data handling: handling PII, securing data, protecting anonymity, balancing interpretability vs. accuracy, generalizing from sample to population
Describe the types of bias that affect the collection and interpretation of data

Suitable for

Designed to equip learners – interns, apprentices, and entry-level data analysts – with the foundational knowledge and skills necessary to perform entry-level data manipulation, analysis, visualization, and communication. With this certificate, candidates could be considered for positions such as entry-level data analysts or researchers, data analytics apprentices or interns, operations research interns, market researchers, and business analysts

Duration

Certificate

IT Specialist – Data Analytics

Governing Body

Pearson (Certiport/IT Specialist program)

Examination Body

Pearson VUE

SKILLING SUITE FEATURES

In-Demand And Up To Date Courseware

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Live Contextualised Labs

Improve the experience by offering a handson, live environment where learners can test their knowledge and practice new skills.

Practice Tests And Exam Pass Pledge

Help learners increase their certification readiness with practice tests designed to improve pass rates. If needed, our Exam Pass Pledge means you can give learners a free retake within 30 days of passing their last practice test.