What you'll get
  • 103+ Hours
  • 20 Courses
  • Course Completion Certificates
  • Self-paced Courses
  • Technical Support
  • Case Studies

Synopsis

  • Participants will gain practical experience in Artificial Intelligence, Machine Learning, Business Intelligence with Tableau, analytics using R and Tableau, and data visualization with SAS/GRAPH.
  • Learners will have access to all course materials for one year.
  • This program is designed for individuals committed to a career in data visualization.
  • Familiarity with R and SAS programming is beneficial but not required.
  • Participants will receive a Course Completion Certificate for each course, as well as verifiable certificates with unique links that can be added to resumes or LinkedIn profiles to highlight their skills.
  • The training is offered as a self-paced video course featuring practical projects for applied learning.

Content

Courses No. of Hours Certificates Details
Data Analytics with QlikView5h 54m✔View Curriculum
QlikView Security Overview1h 1m✔View Curriculum
CloverETL Data Integration2h 7m✔View Curriculum
CloverETL Data Integration - Advanced Case Studies1h 14m✔View Curriculum
EViews - Introductory Econometrics Modeling6h 39m✔View Curriculum
EViews - Advanced17h 12m✔View Curriculum
Courses No. of Hours Certificates Details
Artificial Intelligence and Machine Learning Training Course12h 8m✔View Curriculum
Machine Learning using Python3h 26m✔View Curriculum
Machine Learning - Statistics Essentials8h 23m✔View Curriculum
Business Intelligence with Tableau5h 43m✔View Curriculum
Customer Analytics using R and Tableau2h 7m✔View Curriculum
Pricing Analytics using R and Tableau2h 39m✔View Curriculum
Card Purchase Prediction using R2h 28m✔View Curriculum
Analytics using Tableau9h 28m✔View Curriculum
Courses No. of Hours Certificates Details
Business & Data Analytics - Beginners2h 18m✔View Curriculum
Online Informatica Training: Beginners | Informatica ETL Tools Guide2h 11m✔View Curriculum
Oracle SQL Comprehensive Training17h 32m✔View Curriculum
Graphs & Charts in Microsoft Excel 20102h 18m✔View Curriculum
SAS/GRAPH2h 1m✔View Curriculum
Statistical Tools in Excel1h 11m✔View Curriculum

Description

Data Visualization is the practice of representing data visually to make it easier for viewers to comprehend and interpret. Transforming complex datasets into graphical formats enables information to be communicated clearly and effectively. Common methods of data representation include bar charts, line charts, histograms, pie charts, area charts, control charts, run charts, and box plots, among others. Information can be displayed through graphs, charts, maps, or other visual forms, making insights more accessible and actionable.
In the field of Data Science, Data Visualization plays a crucial role by highlighting patterns, simplifying comparisons, and presenting large volumes of data concisely while eliminating unnecessary details. Its applications span multiple domains, including news website displays, weather updates, public transport information, mind maps, and articles.
A variety of tools are available to create effective visualizations, including Plotly, RAWGraphs, D3.js, Tableau, ChartBlocks, DataWrapper, and Infowrap. These tools allow users to convert raw data into insightful visual representations that improve comprehension and support well-informed decision-making.

Sample Certificate

Course Certification

Requirements

  • The Data Visualization course is intended for those pursuing careers as Data Analysts, Data Scientists, or Software Developers.
  • No strict prerequisites are required. Learners with a basic understanding of Data Science, Statistics, Python programming, or Data Analytics will be able to follow the course.
  • Those interested in data, statistical analysis, or visualization techniques will find the course accessible.
  • A foundational knowledge of Python or another functional programming language for handling large datasets is recommended to maximize learning.
  • Prior experience with data-related techniques, libraries, or frameworks is helpful but not required.
  • Familiarity with Machine Learning concepts, Tableau, or QlikView can enhance the learning experience.
  • Basic knowledge of Python programming, statistical methods, data modeling, or related concepts will help learners grasp the advanced techniques covered in the course.
  • Understanding Python, Machine Learning, or statistical operations strengthens the ability to work with data representation methods and supports further exploration of statistical programming.

Target Audience

  • This Data Visualization course is designed for professionals looking to elevate their expertise and career prospects in data analytics.
  • It benefits students in Engineering, Computer Science, and related fields, as well as graduates from any discipline.
  • Learners with a background in Python, Data Analysis, Statistics, or analytics tools will find the course particularly valuable.
  • The curriculum provides hands-on experience with leading data visualization tools, including Tableau and QlikView, and builds a strong foundation for professional development.
  • This certification is recommended for those aiming to master data analysis techniques and improve their career prospects in analytics.
  • Professionals targeting roles such as Tableau Analyst, Data Scientist, Python Developer, or Business Analyst will gain advanced skills in QlikView, Tableau, Machine Learning, Python, Business Intelligence, ETL operations, SAS, and graphical data representation.
  • The course prepares learners for positions including Tableau Developer, Data Analyst, Statistical Analyst, BI Developer, Reporting Analyst, ODI Developer, and other analytics-focused roles, expanding career opportunities in data analytics.
  • Bachelor’s and Master’s degree holders in Engineering, Science, or related technical fields can use this course to pursue data-driven roles such as Data Analyst, Tableau Developer, or ODI Developer in large organizations, strengthening their technical skills and employability.