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Duration:
Only 7 days
Study Mode:
Classroom
Next Date:
15/01/2025 (Wednesday)

Overview

This accelerated IBM: IBM Data Analytics with Excel and R Professional Certification, will prepare you for a career in data analytics. The topics covered within this certification enable you to:

  • Master the most up-to-date practical skills and knowledge data analysts use in their daily roles
  • Learn how to perform data analysis, including data preparation, statistical analysis, and predictive modeling using R, R Studio, and Jupyter
  • Utilize Excel spreadsheets to perform a variety of data analysis tasks like data wrangling, using pivot tables, data mining, & creating charts
  • Communicate your data findings using various data visualization techniques including, charts, plots & interactive dashboards with Cognos and R Shiny

This course will teach you the foundational data skills employers are seeking for entry level data analytics roles and will provide a portfolio of projects and a Professional Certificate from IBM to showcase your expertise to potential employers.

You’ll learn the latest skills and tools used by professional data analysts and upon successful completion of this program, you will be able to work with Excel spreadsheets, Jupyter Notebooks, and R Studio to analyze data and create visualizations. You will also use the R programming language to complete the entire data analysis process, including data preparation, statistical analysis, data visualization, predictive modeling and creating interactive dashboards. Lastly, you’ll learn how to communicate your data findings and prepare a summary report.

In just 7 days, you’ll also learn how to:

  • Describe the data ecosystem, tasks a Data Analyst performs, as well as skills and tools required to become a successful Data Analyst
  • Explain basic functionality of spreadsheets, and utilize Excel to perform a variety of data analysis tasks like data wrangling, using pivot tables, and data mining
  • Create various types of visualizations including charts, and dashboards using Excel and Cognos Analytics.
  • Perform basic R programming tasks such as using common data structures, data manipulation, using APIs, webscraping, and working with R Studio and Jupyter.
  • Create relational databases and query the data using SQL and R from JupyterLab
  • Complete the data analysis process, including data preparation, statistical analysis, and predictive modeling.
  • Communicate data findings using data visualization charts, plots, and dashboards using libraries such as ggplot, leaflet and R Shiny.

At the end of this course, you’ll sit the IBM exam, and achieve your IBM Data Analytics with Excel and R Professional Certification. Through Firebrand’s Lecture | Lab | Review methodology, you’ll get certified at twice the speed of the traditional training and get access to courseware, learn from certified instructors, and train in a distraction-free environment.

 

Audience

This course is ideal for:

  • Entry level roles in Data Analytics or Data Science.

Curriculum

Module 1: Introduction to Data Analytics

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Module 2: Excel Basics for Data Analysis

  • Display working knowledge of Excel for Data Analysis.
  • Perform basic spreadsheet tasks including navigation, data entry, and using formulas.
  • Employ data quality techniques to import and clean data in Excel.
  • Analyze data in spreadsheets by using filter, sort, look-up functions, as well as pivot tables.

 

Module 3: Data Visualization and Dashboards with Excel and Cognos

  • Create basic visualizations such as line graphs, bar graphs, and pie charts using Excel spreadsheets.
  • Explain the important role charts play in telling a data-driven story.
  • Construct advanced charts and visualizations such as Treemaps, Sparklines, Histogram, Scatter Plots, and Filled Map Charts.
  • Build and share interactive dashboards using Excel and Cognos Analytics.

 

Module 4: Assessment for Data Analysis and Visualization Foundations

  • Demonstrate readiness for performing foundational data analysis and data visualization tasks and key steps in the Data Analytics process.
  • Differentiate between the roles different data professionals play in a modern data ecosystem.
  • Perform basic Excel tasks for Data Analysis including data quality and data preparation skills.
  • Exhibit abilities in visualizing data using Excel and proficiency in creating dashboards using Excel and Cognos Analytics.

 

 

Module 5: Introduction to R Programming for Data Science

  • Manipulate primitive data types in the R programming language using RStudio or Jupyter Notebooks.
  • Control program flow with conditions and loops, write functions, perform character string operations, write regular expressions, handle errors.
  • Construct and manipulate R data structures, including vectors, factors, lists, and data frames.
  • Read, write, and save data files and scrape web pages using R.

 

Module 6: SQL for Data Science with R

  • Create and access a database instance on the cloud
  • Compose and execute basic SQL statements - SELECT, INSERT, UPDATE, DELETE, CREATE, DROP
  • Construct SQL statements to filter, sort, group results, use built-in functions, compose nested queries, access multiple tables
  • Analyze data from Jupyter using R and SQL by combining SQL and R skills to query real-world datasets

 

Module 7: Data Analysis with R

  • Prepare data for analysis by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.
  • Compare and contrast predictive models using simple linear, multiple linear, and polynomial regression methods.
  • Examine data using descriptive statistics, data grouping, analysis of variance (ANOVA), and correlation statistics.
  • Evaluate a model for overfitting and underfitting conditions and tune its performance using regularization and grid search.

 

Module 8: Data Visualization with R

  • Create bar charts, histograms, pie charts, scatter plots, line graphs, box plots, and maps using R and related packages.
  • Design customized charts and plots using annotations, axis titles, text labels, themes, and faceting.
  • Create maps using the Leaflet package for R.
  • Create interactive dashboards using the Shiny package for R.

 

Module 9: Data Science with R - Capstone Project

  • Write a web scraping program to extract data from an HTML file using HTTP requests and convert the data to a data frame.
  • Prepare data for modelling by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.
  • Interpret datawithexploratory data analysis techniques by calculating descriptive statistics, graphing data, and generating correlation statistics.
  • Build a Shiny app containing a Leaflet map and an interactive dashboard then create a presentation on the project to share with your peers.

Exam Track

At the end of this accelerated course, you’ll sit the following exam at the Firebrand Training centre, covered Certification Guarantee:

IBM: IBM Data Analytics with Excel and R Professional Certification Exam

You will complete hands-on labs to build your portfolio and gain practical experience with Excel, Cognos Analytics, SQL, and the R programing language and related libraries for data science, including Tidyverse, Tidymodels, R Shiny, ggplot2, Leaflet, and rvest.

Projects include:

  • Analyzing fleet vehicle inventory data using pivot tables.
  • Using key performance indicator (KPI) data from car sales to create an interactive dashboard.
  • Identifying patterns in countries’ COVID-19 testing data rates using R.
  • Using SQL with the RODBC R package to analyze foreign grain markets.
  • Creating linear and polynomial regression models and comparing them with weather station data to predict precipitation.
  • Using the R Shiny package to create a dashboard that examines trends in census data.
  • Using hypothesis testing and predictive modeling skills to build an interactive dashboard with the R Shiny package and a dynamic Leaflet map widget to investigate how weather affects bike-sharing demand.
  • Submitting this idea will trigger a series of actions for various teams. The product team will review the initial idea and progress it through the life cycle

Prerequisites

Before attending this accelerated course, you should have:

  • No prior experience required, but statistical or programming knowledge is necessary.

What's Included

Your accelerated course includes:

  • Accommodation *
  • Meals, unlimited snacks, beverages, tea and coffee *
  • On-site exams **
  • Exam vouchers **
  • Practice tests **
  • Certification Guarantee ***
  • Courseware
  • Up-to 12 hours of instructor-led training each day
  • 24-hour lab access
  • Digital courseware **

* For residential training only. Accommodation is included from the night before the course starts. This doesn't apply for online courses.
** Some exceptions apply. Please refer to the Exam Track or speak with our experts.
*** Pass first time or train again free as many times as it takes, unlimited for 1 year. Just pay for accommodation, exams, and incidental costs.

Benefits

Seven reasons why you should sit your course with Firebrand Training

  • Two options of training. Choose between residential classroom-based, or online courses
  • You'll be certified fast. With us, you’ll be trained in record time
  • Our course is all-inclusive. A one-off fee covers all course materials, exams**, accommodation* and meals*. No hidden extras.
  • Pass the first time or train again for free. This is our guarantee. We’re confident you’ll pass your course the first time. But if not, come back within a year and only pay for accommodation, exams and incidental costs
  • You’ll learn more. A day with a traditional training provider generally runs from 9 am – 5 pm, with a nice long break for lunch. With Firebrand Training you’ll get at least 12 hours/day of quality learning time, with your instructor
  • You’ll learn faster. Chances are, you’ll have a different learning style to those around you. We combine visual, auditory and tactile styles to deliver the material in a way that ensures you will learn faster and more easily
  • You’ll be studying with the best. We’ve been named in the Training Industry’s “Top 20 IT Training Companies of the Year” every year since 2010. As well as winning many more awards, we’ve trained and certified over 135,000 professionals

*For residential training only. Doesn't apply for online courses
**Some exceptions apply. Please refer to the Exam Track or speak with our experts

Think you are ready for the course? Take a FREE practice test to assess your knowledge!  Free Practice Test

Course Dates


Start
Finish
Status
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15/01/2025 (Wed)
21/01/2025 (Tue)
Open
Classroom
15/04/2025 (Tue)
21/04/2025 (Mon)
Open
Classroom
16/07/2025 (Wed)
22/07/2025 (Tue)
Open
Classroom
20/10/2025 (Mon)
26/10/2025 (Sun)
Open
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