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A Detailed Guide To The IBM Data Analytics Course

By utilizing the power of data, organizations all across the world are exploring new prospects. Big data analytics specialists are essential to these expanding enterprises because of the volume, pace, and variety of data being created today. Organizations all over the world are embracing the cloud in a big manner, and there is a growing need for qualified personnel. Completing the IBM Data Analytics course might give you a jump start in this lucrative career. One of the best data analytics certificate programs advised for aspiring data analysts is the IBM Data Analyst Professional Certificate. More than nine data analysts who currently work for or previously worked for IBM have developed it. This course is accessible to everyone on the Coursera platform.

IBM Data Analytics Course

Uses of Data Analytics

  • Data is used by telecom providers to analyze location-based devices for revenue assurance. Telecom firms can use big data to enhance their operations in several different areas, including price optimization, network growth, and add-ons.
  • Data is used by healthcare institutions to tailor treatment approaches, anticipate patient admission trends, and enhance clinical research.
  • Data is used by financial services companies for algorithmic trading, risk assessment, fraud detection, and security threat detection in addition to customer analytics to personalize offers.
  • Data is used by businesses in the retail, gaming, and entertainment industries to improve targeted advertising and lower the cost of customer acquisition.

IBM Data Analytics Course – An Introduction

This Professional Certificate is appropriate for learners with or without college degrees and does not require any prior programming or statistics expertise. Basic computer literacy, high school math, comfort with numbers, a willingness to study, and a desire to enhance your profile with useful abilities are all you need to get started. By mastering the fundamentals of data analysis and developing practical abilities and experience, you can advance your career as a data analyst. After completing this program, you’ll have the confidence and portfolio needed to start a job as an associate or junior data analyst because you’ll have examined real-world datasets, built interactive dashboards, and shared reports to discuss your findings. Additionally, you’ll lay the groundwork for additional data disciplines like data science or data analysis.

You will discover the essential elements of data analysis throughout this course. You’ll begin studying data collection methodology and developing your ability to identify data sources. The use of dashboard tools and visualizations will next be discussed, along with methods for sharing, cleaning, and analyzing data. Everything comes together in the final project, which includes a test of your understanding of the course material, an examination of what it means to be a data analyst, and a scenario for using data analysis in the real world.

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IBM Data Analytics Course – Objectives

  • Excel skill is required to carry out several data analysis tasks, such as data wrangling and data mining.
  • Build dashboards with IBM Cognos Analytics and numerous Excel charts and plots. Utilize Python packages like Matplotlib to visualize data.
  • Learn the basics of Python so you can use libraries like Pandas and Numpy to analyze data and call APIs and Web Services.
  • Explain the data ecology. Create queries in Jupyter notebooks that use SQL and Python to access data in cloud databases.

IBM Data Analytics Course – Modules

The IBM Data Analyst Professional Certificate consists of 8 modules in total plus a capstone project. Instead of needing to take the IBM data analyst course in its entirety, students have the choice to take any one of these eight courses independently.

1. Introduction to Data Analytics – 10 hrs

The fundamentals of data analysis, the job of a data analyst, and the tools that are employed to carry out everyday tasks are all introduced in a friendly manner in this course. You will learn the basics of data analysis, such as data mining and data gathering, as well as the data ecosystem.

You will be better able to distinguish between the responsibilities of a Data Engineer, Data Scientist, and Data Analyst. You will be able to enumerate the databases and data warehouses that make up the data ecosystem. Finding the major participants in the data ecosystem and researching the various local and internet technologies are the next steps.

There is no prerequisite for this course in spreadsheets, computer science, or data analysis. Basic computer literacy, math skills equivalent to those found in high school, and access to a cutting-edge web browser like Chrome or Firefox are all you need to get started.

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2. Excel Basics for Data Analysis – 12 hrs

You will learn the fundamentals of using Excel spreadsheets for data analysis in this course. It discusses some of the initial stages for using spreadsheets and how to use them while evaluating data. You can learn a lot from the videos, demos, and examples included in the guide before using the step-by-step instructions to practice on a real spreadsheet. For working with data, whether for business, marketing, data analytics, or research, Excel is a crucial tool. This course begins with an introduction to spreadsheet programs like Google Sheets and Microsoft Excel as well as loading data from various formats.

Following this introduction, you will learn to carry out some fundamental data wrangling and cleansing activities and advance your understanding of data analysis by using pivot tables, filtering, and sorting within the spreadsheet. You will gain knowledge of how spreadsheets may be utilized as a data analysis tool and its limitations by completing these exercises throughout the course.

Understanding the functions of data formatting will help you clean and analyze your data more quickly. To organize and make your data readable, you will then convert your data to a pivot table and learn how to use its capabilities. You can demonstrate your newly gained data analysis abilities in the final project.

In this course, learning Excel is made simple. It doesn’t call for any prior spreadsheet or code knowledge. Additionally, no program downloads or installations are necessary. To access Excel online for free, all you need is a computer with a recent web browser and the ability to set up a Microsoft account. However, you may also easily follow along if you already own a desktop version of Excel.

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3. Data Visualization and Dashboards with Cognos and Excel – 9 hrs

Some of the basic steps in creating data visualizations using spreadsheets and dashboards are covered in this course. Create one of the many different types of charts that are available in spreadsheet programs like Excel to start the process of constructing a story with your data. Examine the many spreadsheet tools, including the pivot function and the ability to build dashboards, and discover how each one has a special power to modify your data.

You will have a fundamental understanding of using spreadsheets as a tool for data visualization after finishing this course. You will develop the skills necessary to produce data visualizations successfully, such as charts and graphs, and you’ll start to realize how important they are for conveying the results of your data research. There are many practical labs in this course, as well as a final project.

The course will conclude with you using IBM Cognos Analytics to create a collection of data visualizations and an interactive dashboard that can be shown to peers, professional communities, or potential employers. Learn how to create simple and sophisticated charts through each lab, and as you progress through the course, you’ll start building dashboards using spreadsheets and IBM Cognos Analytics.

There is no prerequisite for this course in computer science or data analysis. A high school diploma in arithmetic, a modern web browser like Chrome or Firefox, the ability to create a Microsoft account to access Excel for the Web, and a fundamental understanding of Excel spreadsheets are all you need to get started.

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4. Python for AI, Data Science, and Development – 22 hrs

One of the most widely used programming languages in the world is Python, and there has never been a higher demand for individuals who can use Python’s principles to power business solutions across industries. You don’t need any prior programming knowledge for this course; you’ll learn how to write in Python from scratch in a couple of hours!

You will master the essentials of Python, such as data structures and data analysis, finish practical exercises spread throughout the modules, and produce a final project to showcase your newly acquired knowledge. By the end of this course, you’ll be confident using Python to build simple programs, manipulate data, and address practical issues. You’ll receive a solid basis for further study in the area and acquire abilities to boost your profession. Completing this module will make you eligible for the following courses:

  • IBM Applied AI Professional Certificate 
  • Applied Data Science Specialization 
  • IBM Data Science Professional Certificate

5. Python Project for Data Science – 8 hrs

You are expected to exhibit basic data-working Python skills after completing this mini-course. As part of the final project for this course, you will use Python to create a straightforward dashboard. The IBM Data Science Professional Certificate and the IBM Data Analytics Professional Certificate both include this course. This course does not include a lot of instructional material and is not meant to teach you Python. You are expected to use your prior Python skills.

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6. SQL and Databases for Data Science with Python – 37 hrs

For data specialists like Data Analysts, Data Scientists, and Data Engineers, having a working knowledge of SQL (or Structured Query Language) is essential. Databases house a large portion of the world’s data. For interacting with and extracting data from databases, SQL is a potent language.

You will cover every aspect of SQL in this course, from the most fundamental Select statements to more complex ideas like JOINs. You will experience writing SQL queries, dealing with actual databases on the Cloud, and employing real data science tools through practical labs and projects. You will exhibit your abilities by analyzing several real-world datasets for the final project.

7. Data Analysis with Python – 14 hrs

Python data analysis is a crucial ability for data analysts and data scientists. You will learn the fundamentals of data analysis using Python in this course before developing and analyzing data models. You will learn how to perform exploratory data analysis (EDA), clean and manage data, import data from various sources, and produce useful data visualizations.

The next step is to create linear, multiple, and polynomial regression models & pipelines and learn how to evaluate them to forecast future trends from data. To import, modify, analyze, and visualize fascinating datasets, you will use a variety of open-source Python modules, such as Pandas and Numpy.

From the fundamentals of data analysis using Python to creating and assessing data models, this course will guide you in:

  • Data collection and import, 
  • Data preparation and formatting, 
  • Data frame manipulation
  • Data summarization
  • Constructing data pipelines; 
  • Developing machine learning regression models
  • Fine-tuning models

8. Data Visualization with Python – 17 hrs

You will master a variety of techniques in this course for efficiently visualizing both small- and large-scale data. You will be able to take data that doesn’t seem to have much relevance at first and display it in a way that reveals insights. You will learn how to use a variety of Data Visualization tools and techniques in this course.

You’ll discover how to make a variety of fundamental and sophisticated graphs and charts, including Waffle Charts, Histograms, Area Plots, Bar Charts, Word Clouds, Pie Charts, Scatter Plots, Choropleth Maps, and many more! Additionally, you’ll develop interactive dashboards that even those with no prior knowledge of data science can use to better understand the information and make more sensible decisions.

9. IBM Data Analyst Capstone Project – 21 hr

You will put a variety of Data Analytics skills and techniques you’ve learned throughout the IBM Data Analyst Professional Certificate’s earlier courses to use in this course. You will be responsible for gathering data from various sources, performing exploratory data analysis, cleaning and preparing the data, statistically analyzing the data, visualizing the data with charts and plots, and developing an interactive dashboard.

The project will be completed with a presentation of your data analysis report, complete with an executive summary for each organizational stakeholder. Both the final output and your work for the various Data Analysis process phases will be taken into consideration when evaluating you.

Applied Learning Project of IBM Data Analytics Course

You will work on practical projects and laboratories throughout the program to develop the technical abilities needed to collect, manage, mine, and visualize data as well as the soft skills necessary to collaborate with stakeholders and use data storytelling to captivate an audience.

Projects

  • Utilizing Excel pivot tables, import, clean, and evaluate the inventory of fleet vehicles.
  • Create an interactive dashboard with visuals using data from the key performance indicator (KPI) for auto sales.
  • Utilizing the Python data analysis tool Pandas, to extract and graph financial data.
  • To query demographic data sets from the census, crimes, and schools, use SQL.
  • Use data science Python modules to wrangle data, draw charts, and produce regression models to forecast home prices.
  • Make a dynamic Python dashboard to track, report, and enhance domestic flying in the US.

You finish a practical capstone project intended to demonstrate your newly acquired data analyst skills at the program’s conclusion.

IBM Data Analytics Course – Duration and Fees

The length of time and rate of learning will determine how much the IBM data analyst certification will cost. This course can be finished by students in 1, 3, or 6 months. If you choose to take the course for one month or six months, it would cost you anywhere between INR 2,943 and INR 8,830.

IBM Data Analytics Course – Skills

  • Microsoft Excel
  • Python Programming
  • Data Analysis
  • Data Visualization
  • SQL
  • Data Science
  • Spreadsheet
  • Pivot Table
  • IBM Cognos Analytics
  • Dashboard
  • Pandas Numpy

IBM Data Analytics Course – Features

  • Taught by top companies and universities
  • Affordable programs
  • Apply your skills with hands-on projects
  • Learn about your schedule
  • Course videos and readings
  • Graded quizzes and assignments
  • Shareable Certificate upon completion

IBM Data Analytics Course – Certification

Upon completion of the course, you will receive a shareable certificate, On printed resumes, CVs, and other papers, as well as in the Certifications part of your LinkedIn page, you can share your Certificate.

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FAQs

1. Is the IBM Data Analytics course, worth it?

One of the top data analytics certificates available on Coursera is the IBM Data Analyst Professional Certificate –

  • Over 0.65 lakh students have registered for the course, which has an overall rating of 4.6/5.
  • Nine teachers in total have selected the content for this course. The instructors are all IBM employees who are either professionals or data analysts.
  • Since the aspirant is a total newbie, the course modules are designed with that in mind; as a result, everything is taught through real-world examples and interactive video lectures.

2. List the prospective job profiles that one may apply for after completing this IBM Data Analytics course.

Aspirants become eligible for the following positions after completing the IBM Data Analytics course:

Business Analyst
Role: Subject Matter  Business users/knowledge workers; subject matter experts 

Competence: Needs self-service access to end-user analytics tools and data

Data Scientist
Role: Deploy and develop analytic models
Competence: Deep understanding of quants

Application Developer
Role: Programmer who can operationalize repeatable analytics
Competence: Needs an accurate sense of requirements for business analytic capabilities

Data Engineer
Role: Manages the data, and builds logical and physical models
Competence: Responsible for the integration tasks defined by business needs

Chief Data Officer (CDO)
Role: Executive owner of the data, who delegates the definition of governance rules, logical business object models, and data access policies to data engineers
Competence: Responsible for the quality of data and regulatory compliance

3. What prior knowledge is required to enroll in this IBM Data Analytics course?

No specialized training or education is required to enroll in this course. However, you should be familiar with the fundamentals of computers, have high-school-level arithmetic skills, and feel at ease dealing with numbers.

Conclusion

Data analytics is the process of gathering, organizing, and analyzing data to make informed decisions or forecast the future. The best approach to learning about data analytics is to enroll in a certification program. With the help of this IBM Data Analytics course, you can position yourself to compete in the booming job market for data analysts, which will experience a 20% growth through 2028. (U.S. Bureau of Labor Statistics). After finishing this Professional Certificate, you will be prepared to begin working in a Data Analytics entry-level position. Your existing work can benefit from applying your newly learned analytical abilities in a range of fields, including banking, accounting, and IT, as well as positions like marketing, finance, and research.

Having done my Masters in English Literature, from the University of Calcutta, I always have had a love for reading and a flair for writing. My strong academic results made me inclined toward academic jobs, but my love for writing lingered. I have worked as an Assistant Profesor in Business Communications in different colleges over the years. Now I am pursuing my passion for writing. Articles, Blogs, and Content creation make me explore this passion to the fullest. I have successfully completed the Content Writing Master Course Certification from IIM Skills. I am trying to gain a strong foothold in the world of Digital Content Creation.

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