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ITS Data Analytics

4.6 out of 5 rating Last updated 30/05/2024   English

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Find out more about this course

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3 Days

18 CPD hours


This Pearson CertPREP 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. This course consists of lessons accompanied by videos to help learners achieve their learning goals. 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. The knowledge and skills garnered by learners

Lesson 1: Data Basics
  • Skill 1.1: Define the concept of data.
  • Define data and information.
  • Differentiate between data and information.  Define statistics and its relation to data.
  • Skill 1.2: Describe basic data variable types.
  • Define variables.
  • Identify different data types.  Define type checking.
  • Skill 1.3: Describe basic structures used in data analytics.
  • Define tables.
  • Define arrays.  Define lists.
  • Skill 1.4: Describe data categories.
  • Differentiate between structured and unstructured data.  Identify and use different types of data.
Lesson 2: Data Manipulation
  • Skill 2.1: Import, store, and export data.
  • Describe ETL processing.
  • Perform ETL with relational data.
  • Perform ETL with data stored in delimited files.  Perform ETL with data stored in XML files.
  • Perform ETL with data stored in JSON files.
  • Skill 2.2: Clean data.
  • Perform data cleaning common practices.  Perform truncation.
  • Describe data validation.
  • Skill 2.3: Organize data.
  • Describe data organization.
  • Perform sorting.
  • Perform filtering.
  • Perform appending and slicing.  Perform pivoting.
  • Perform transposition.
  • Skill 2.4: Aggregate data.
  • Describe the aggregation function.
  • Use aggregation functions like COUNT, SUM, MIN, MAX, and AVG in SQL.  Use GROUP BY and HAVING in SQL.
Lesson 3: Data Analysis
  • Skill 3.1: Describe and differentiate between types of data analysis.
  • Perform descriptive analysis.
  • Perform diagnostic analysis.
  • Perform predictive analysis.
  • Perform prescriptive analysis.  Perform hypothesis testing.
  • Skill 3.2: Describe and differentiate between data aggregation and interpretation metrics.
  • Define data aggregation and data interpretation.  Define data interpretation.
  • Describe data aggregation and interpretation metrics.
  • Skill 3.3: Describe and differentiate between exploratory data analysis methods.
  • Find relationships in a dataset.  Identify outliers in a dataset.
  • Drill a dataset.
  • Mine a dataset.
  • Skill 3.4: Evaluate and explain the results of data analyses.
  • Perform a simple linear regression.
  • Interpret the results of a simple linear regression.  Use regression analysis for prediction.
  • Skill 3.5: Define and describe the role of artificial intelligence in data analysis.
  • Define artificial intelligence, algorithm, machine learning, and deep learning.
  • Discuss how machine learning algorithms help in data analysis.
  • Discuss how artificial intelligence algorithms work in data analysis.
Lesson 4: Data Visualization and Communication
  • Skill 4.1: Report data.
  • Use tables and charts to display information.  Disaggregate data.
  • Skill 4.2a and 4.3a: Create and derive conclusions from visualizations that compare one or more categories of data.
  • Use different types of charts:  Column chart.  Bar chart.
  • Skill 4.2b and 4.3b: Create and derive conclusions from visualizations that show how individual parts make up the whole.
  • Differentiate between the following types of graphical representations:  Pie Chart.
  • Donut Chart.
  • Other variations on bar and column charts such as stacked bar and column charts.
  • Skill 4.2c and 4.3c: Create and derive conclusions from visualizations that analyze trends.
  • Use different types of visualization:
  • Line chart and variants of the line chart.  Waterfall chart.
  • Sankey Diagram.
  • Skill 4.2d and 4.3d: Create and derive conclusions from visualizations that determine the distribution of data.
  • Use different types of visualizations:  Histograms.
  • Box and Whisker plot.
  • Skill 4.2e and 4.3e: Create and derive conclusions from visualizations that analyze the relationship between sets of values.
  • Use different types of visualizations:
  • Scatter plot.
  • Bubble chart.
Lesson 5: Responsible Analytics Practice
  • Skill 5.1: Describe data privacy laws and best practices:  Describe the fair information practice principles.
  • Understand data privacy laws in the US.
  • Understand data privacy laws in Canada.  Understand data privacy laws in the EU.
  • Skill 5.2: Describe best practices for responsible data handling:  Handle PII, secure data, and protect anonymity within small datasets.  Balance the trade-off between interpretability and accuracy.  Generalize from a sample to a population.
  • Skill 5.3: Given a scenario, describe the types of bias that affect the collection and interpretation of data.
  • Explain and identify different types of bias that affect the gathering of data.
Additional course details:

Nexus Humans ITS Data Analytics training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward.

This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts.

Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.

While we feel this is the best course for the ITS Data Analytics course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.

Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

FAQ for the ITS Data Analytics Course

Available Delivery Options for the ITS Data Analytics training.
  • Live Instructor Led Classroom Online (Live Online)
  • Traditional Instructor Led Classroom (TILT/ILT)
  • Delivery at your offices in London or anywhere in the UK
  • Private dedicated course as works for your staff.
What certification does the ITS Data Analytics training prepare you for?

The ITS Data Analytics training course helps prepare you for the ITS Data Analytics certification path.

How many CPD hours does the ITS Data Analytics training provide?

The 3 day. ITS Data Analytics training course give you up to 18 CPD hours/structured learning hours. If you need a letter or certificate in a particular format for your association, organisation or professional body please just ask.

What is the correct audience for the ITS Data Analytics training?

This course is 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, bvisualization, and communication. With the Data Analytics certificate, you 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.

Do you provide training for the ITS Data Analytics.

Yes we provide corporate training, dedicated training and closed classes for the ITS Data Analytics. This can take place anywhere in Ireland including, Dublin, Cork, Galway, Northern Ireland or live online allowing you to have your teams from across Ireland or further afield to attend a single training event saving travel and delivery expenses.

What is the duration of the ITS Data Analytics program.

The ITS Data Analytics training takes place over 3 day(s), with each day lasting approximately 8 hours including small and lunch breaks to ensure that the delegates get the most out of the day.

Why are Nexus Human the best provider for the ITS Data Analytics?
Nexus Human are recognised as one of the best training companies as they and their trainers have won and hold many awards and titles including having previously won the Small Firms Best Trainer award, national training partner of the year for Ireland on multiple occasions, having trainers in the global top 30 instructor awards in 2012, 2019 and 2021. Nexus Human has also been nominated for the Tech Excellence awards multiple times. Learning Performance institute (LPI) external training provider sponsor 2024.
Is there a discount code for the ITS Data Analytics training.

Yes, the discount code PENPAL5 is currently available for the ITS Data Analytics training. Other discount codes may also be available but only one discount code or special offer can be used for each booking. This discount code is available for companies and individuals.

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Training Insurance Included!

When you organise training, we understand that there is a risk that some people may fall ill, become unavailable. To mitigate the risk we include training insurance for each delegate enrolled on our public schedule, they are welcome to sit on the same Public class within 6 months at no charge, if the case arises.

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