Data Analytics Certification Course with R, Excel & Tableau

Acadgild’s Data Analytics Course will transform you into a skilled data analyst in just three months. It’s comprehensively designed to train you in all the essentials of the field and provide plenty of hands-on experience.

72+ hrs
Live Mentoring
200+ hrs
Coding Assignments
Real Time Projects
Industry Cases
Coding Support


18 Weeks
Total Duration
Course Price



Programming in R (6 Hrs)

  • Basics of R
  • Conditional and loops
  • R packages/libraries
  • Data mining GUI in R
  • Data structures in R
  • Exceptions/ debugging in R

Data analysts must know how to work with R which is not only the most popular programming language used for data analysis but also an indispensable IT skill.

Data Wrangling (6 Hrs)

  • Reading CSV, JSON, XML, .XLSX and HTML files using R
  • ETL operations in R
  • Sorting/ merging data in R
  • Cleaning data
  • Data management using dplyr in R

Once you have covered the nuances of R, you will learn the intricacies of working with data through wrangling and visualizing them

Statistics and Probability (6 Hrs)

  • Descriptive statistics, random variables, and probability distribution functions
  • Data distributions like uniform, binomial, exponential, poisson, etc
  • Probability concepts, set theory and hypothesis testing
  • Central limit theorem, t-test, chi-square, z-test
  • Central limit theorem

Any aspiring data analyst should have good grasp over statistics as it’s impossible to work with data otherwise. It’s crucial to know how to employ statistical analysis while collecting, organizing and analyzing data so that insightful interpretations can be derived.

Modeling in R (10 Hrs)

  • Linear regression model in R
  • Multiple linear regressions model
  • Representation of regression results
  • Non-linear regression models
  • Tree-based regression models
  • Decision tree-based models
  • Rule-based systems

Regression models play an integral role in data-driven decision making for any analyst. This unit will emphasize on all about modeling in R.

Mining Algorithms Using R (8 Hrs)

  • Association analysis
  • Market-based analysis/ rules
  • Apriori algorithm
  • Ensemble models - random forest model, boosting model
  • Segmentation analysis- types of segmentation, k-means clustering, Bayesian clustering.
  • Feature selection/ dimension reduction- multidimensional scaling, dimension reduction, factor or
  • component analysis.
  • Axes
  • Covariance

Algorithms can determine interesting patterns from large datasets during data mining. Having a deep understanding of how these algorithms work and ways to use them effectively is necessary during data analysis.

Time Series Forecasting in R and Model Deployment (8 Hrs)

  • Basics of time series
  • Components of time series
  • Time series forecasting
  • Deploying predictive models
  • Using SQL server
  • Using external tools
  • Using big data tools
  • Integrating R with Hadoop/Spark

Time series forecasting helps analysts to make business forecasts based on historical data patterns. This aids in shaping future business goals and predicting market behavior.

Data Wrangling using SQL and Excel (20 Hrs)

  • SQL queries
  • Integrating with R
  • Deployment and execution
  • Data modeling and formatting using Excel
  • Excel formulas to perform analytics
  • Macros for job automation

Transforming data into actionable information using SQL and Excel will help extract information required to effectively transform data into actionable information.

Data Analysis and Visualization using Tableau (8 Hrs)

  • Introduction to Tableau and its layout
  • Connecting tableau to files and databases
  • Data filters in Tableau
  • Calculation and parameters
  • Tableau graphs and maps
  • Creating Tableau dashboard
  • Data blending
  • Creating superimposed graphs
  • Integrating Tableau with R

Simple visualization makes it easy to represent even the most complicated datasets. Tools like Tableau can aid in this process.

Capstone Project (2 Hrs)

The course culminates in an enterprise-level project for a fictitious client that will expose you to every stage of the data analytics process. Every student is guided by industry experts as they bring their personal projects to life. Alternately, students may choose to work on a live project from their organization. Our students generally come from varying backgrounds. We encourage all our students to pursue projects that are best suited for their careers and domains. The project is an opportunity for you to test your skills and demonstrate your ability to invent solutions for real world problems

Speak to our course advisor if you have queries

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Expert Mentors conduct live sessions throughout the course
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Our support team will be there for you around-the-clock to help you with doubts.

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100% Job Placement Assistance
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What is the experience of doing Data Analytics with R, Excel, and Tableau course at Acadgild like?

Joining a data analyst course will greatly aid students to build interesting portfolios so that they land their dream jobs they. The data analyst course from Acadgild contains all the information and knowledge packaged in a holistic manner so that students can perform best in their careers.

Whether you are a seasoned professional, fresher or someone seeking to upskill themselves in new technologies, the data analyst course can help you learn more and do more with your career. The data analyst course is designed in such a way that the students get the best out of this course. For this, Acadgild has a coding support team to aid them in case they encounter any roadblock. Another plus is the free job assistance program where you would get a coach to groom and make you industry-ready. This network of professionals also helps students to be aware of employment opportunities. Enroll Now for the course Data Analytics with R, Excel, and Tableau.

What is this course about?

This course teaches techniques of data analysis and communication using Tableau, and Excel. It covers key concepts and provides practical experience via real-time projects to help develop skills that are relevant and useful for careers in data analytics.

Who should take this course?

The course is suited for anyone with a zeal to learn about data analytics. It is ideal for aspiring data analysts from non-technical backgrounds as it does not involve programming. Our students are generally managers and other business executives looking to learn how they can use data to garner business intelligence.

What are the prerequisites for this course?

Basic knowledge of math and statistics.

Why should I take this course?

Acadgild provides quality training to anyone with the zeal to learn. We offer a great platform for you to master Data Analytics. Our courses have world class content, offer a gamified learning experience, and include real-time projects to help you gain practical exposure. Additionally, you will be mentored by leading experts in the industry and will have support around-the-clock from SMEs (Subject Matter Experts) to help resolve your queries.

What is the difference b/w Data Analytics course and the Data Science course? (DATA ANALYTICS COURSE)

The data Analytics course explains techniques for data analysis and communication using technologies like R, Tableau, and Excel. Whereas the Data Science course focuses on processes like Data cleansing and processing, predictive modeling, statistical analysis, correlating incongruent data, visualization using Python programming language, and topic like machine learning and Deep Learning.

Will I develop my own project while taking this course?

Yes, you may. Our curriculum is comprehensive and will make you capable to create your own project. Our support staff is also committed to help you along the way. Alternately, you can work on one of the projects in our repertoire to implement what you learn.

How can I get a demo of the course?

You can view a recorded demo session in the Course Overview section. Alternately, you can sign up for a live demo there.

What are the job prospects after doing this course? Will I have to supplement this course with another?

The course will make you proficient in:
  • Data Manipulation
  • Exploratory Data Analysis
  • Data Visualization
  • Linear Models
  • Data Analytics with Visualization using Tableau
You don't need to follow this course with another. This course covers most of the skills required to help you land a lucrative job as a data professional.

What is the difference b/w Big data analytics & Big data Engineering?

Data Analytics is the combination of Data Engineering and Data Science. The lines are blur between the analytics and engineering of data. The reason is the overlapping skills of the professionals in both the fields. Nevertheless, following are the basic differences:
Big Data Engineers create platform for “Big Data” Analysis. They usually design, develop and assimilate data from various resources. The chief responsibility of Data Engineers is to optimize the big data system. It includes the creation of data warehouse to ease the data accessibility for analysis.
Some of the frequently used tools for data engineering are Hadoop, NoSQL, MapReduce and MySQL. Knowledge of ETL Tools, like StitchData or Segment is immensely valuable amongst data engineering jobs.

On the other hand,

Big Data Analytics mostly deals with collecting, manipulating and analyzing data. The key task of a Data Analyst is preparing reports. These reports could be presented through various formats like graphs, charts, dashboards and infographics.
Some of the vital and in-demand software, querying and statistical languages includes; Matlab, Python, SQL, Hive, Pig, Excel, SAS, R, SPSS
The key responsibility of data analysts is to recognize, assess and implement services and tools from external sources. This is to help data validation and cleansing.

Tell me more about the Job Placement Assistance Program.

Our job placement program offers students one-on-one career counselling, and the chance to work with our corporate partners.
Candidates who fulfill the following criteria will be eligible for the program:
• Scored 75% marks or above (resulting in a Platinum certificate) in the course.
• Successfully completed at least 2 quality projects.
• Scored 80% in all the mock technical interviews.
• Was never found plagiarizing code.

*This feature is currently available only for students in India.

What if I miss a class?

All sessions are recorded and uploaded to the course dashboard for you to access at your convenience.

Can I choose my mentors?

Our mentors are top-notch industry professionals with at least 5 years of experience. You will be taught by the best in all batches.

Does Acadgild offer any free resources on Data Analytics?

Yes, we offer free resources like e-books, and blog articles on generic and technical topics by SMEs. You may view these in the free resources section -

How do I make the payment for this course?

You can pay after registering for the course. We accept most credit and debit cards. You can also pay via net banking. Our payment portal has an EMI option if you wish to pay in installments.

What is the Refer and Earn program?

Our ‘Refer and Earn' program gives you a discount on the course fees when your references join us. You may refer students by writing to us at
The details of the Refer and Earn policy can be found at

What is the Refund Policy?

To request a refund, write to us at You may apply for a refund in the first three days after paying the fees. No requests will be entertained after this initial period. The terms and conditions of AcadGild's refund policy may be revised without prior notice. Please check websites for updates on this policy.

How do I request for more information?

You can write to us at with your contact details. Our representatives generally respond to requests within 24 hours.