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Data Analyst

Course Information

Start Date Anytime
End Date 3 Month Access
Mode Self-Paced E-Learning
Fee $1,299 (excluding GST)
Contact 6720 3333 (Ms. Felicia) training.aventis@gmail.com
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LIVE Stream

Course Overview

IBM is the second-largest Predictive Analytics and Machine Learning solutions provider globally (source: The Forrester Wave report, September 2018). A joint partnership with Simplilearn and IBM introduces students to integrated blended learning, making them experts in Data Analytics and Data Science. The Data Analyst Master’s program in collaboration with IBM will make students industry ready for Data Analytics and Data Science job roles.

IBM is a leading cognitive solution and cloud platform company, headquartered in Armonk, New York, offering a plethora of technology and consulting services. Each year, IBM invests $6 billion in research and development and has achieved five Nobel prizes, nine US National Medals of Technology, five US National Medals of Science, six Turing Awards, and 10 Inductions in US Inventors Hall of Fame.

Simplilearn’s Data Analyst Master’s program developed in collaboration with IBM will provide you with extensive expertise in the booming data analytics field. This Data Analyst certification training course will teach you how to master descriptive and inferential statistics, hypothesis testing, regression analysis, data blending, data extracts, and forecasting. Through this course, you will also gain expertise in data visualization techniques using Tableau and Power BI, learning how to organize data and design dashboards. 

In this Data Analyst certification online course, a special emphasis is placed on those currently employed in the non-technical workforce. Through this course, those with a basic understanding of mathematical concepts will be able to complete the course and become an expert in data analytics.

This learning experience melds the knowledge of Data Analytics with hands-on demos and projects via CloudLab. Upon completing this course, you will have all the skills required to become a successful Data Analyst.

This self-paced E learning course is done in partnership with SimpliLearn with over 120 hours of live interactive learning by industry experts.


Aspiring professionals of any educational background with an analytical frame of mind are best suited to pursue the Data Analyst course, including:

  • IT professionals
  • Banking and finance professionals
  • Marketing managers
  • Sales professionals
  • Supply chain network managers
  • Beginners in the data analytics domain
  • Students in UG/ PG programs

Professionals wishing to succeed in this Data Analyst certification training should have basic knowledge of mathematics.

Course Content

Course 1: Introduction

0.1 Course Introduction

0.2 Data Analytics Overview

0.3 Dealing with different types of data

0.4 Data visualization for decision-making

0.5 Data science, data analytics, and machine learning

0.6 Data science methodology

0.7 Data analytics in different sectors

0.8 Analytics framework and latest trends


Course 2: Business Analytics with Excel

0.1 Introduction to Business Analytics

0.2 Formatting conditional formatting and important functions

0.3 Analyzing data with pivot tables

0.4 Dashboarding

0.5 Business analytics with excel

0.6 Data analysis using statistics

0.7 Power BI


Course 3: Tableau Training

0.1 Introduction

0.2 Getting started with Tableau

0.3 Core topics in Tableau

0.4 Creating charts in Tableau

0.5 Working with metadata

0.6 Filters in Tableau

0.7 Applying analytics to the worksheet

0.8 Dashboards

0.9 Modifications to data connections

10. Level of detail


Course 4: Power BI

Microsoft Power BI Recipes

0.1 Get & prep data like a super nerd

0.2 Develop your data nerd process

0.3 Developing reports and dashboards

0.4 Tips, tricks and capstone projects

Microsoft Power BI Desktop

0.1 Online data nerds

0.2 Being the data nerd of your term

Power BI course resources


Course 5: (Section 1) Programming Basics and Data Analytics with Python (self-learning)

0.1/0.2 Learning objective & Introduction

0.3 Data wrangling

0.4 Exploratory data analysis

0.5 Model development

0.6 Model evaluation 

(Section 2) Programming Basics and Data Analytics with Python (live classes)

0.1/0.2 Introduction to course & Programming

0.3 Programming environment setup

0.4 OOPs concept with Python

0.5 Programming fundamentals of Python

0.6 File handling, exception handling and package handling

0.7 Data analytics overview

0.8 Statistical computing

0.9 Mathematical computing using NumPy

10 Data manipulation with Pandas

11 Data visualization with Python

12 Introduction to model building

Practice projects

Free Course: Python for Data Science, Data Visualization with Python


Course 6: Data Science with R Programming

0.1/0.2 Introduction to Business Analytics

0.3 Introduction to R Programming

0.4 Data structures

0.5 Data visualization

0.6 Statistics for Data Science-I

0.7 Statistics for Data Science-II

0.8 Regression analysis

0.9 Classification

10 Clustering

11 Association

Free Course: Math Refresher, Statistics Essential for Data Science


Course 7: Data Analyst Capstone