• mentor 72 +hrs. Live Mentoring
  • code 200 +hrs. Coding Assignments
  • session 5 + Real-Life Projects
  • session 3 + Industry Cases
  • coding-support 24x7 Coding Support
72+hrs. Live Mentoring
200 +hrs. Coding Assignments
5 +
Real-Time Projects
24x7 Coding Support
  • R
  • Tableau
  • Excel
  • sql
  • 18 weeks Total Duration
  • 10-15 hrs/week Effort
18 weeks
Total Duration
999 (All inclusive)
Course Price
  • 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.
  • 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
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
    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
    Job Assistance

    After completing your assignments and projects, we will provide you with one-on-one career guidance, conduct mock interviews and help you build a professional online portfolio to help you get noticed by top recruiters.

    Resume Building

    Learn what to put in your resume and how to get noticed on top job portals from industry experts.

    Online Reputation Building

    Establish your presence on all the right social networks like Git, Stack Overflow, LinkedIn, etc

    Mock Interviews

    Get insider tips on how to ace interviews at top firms.

    Landing a Job

    Work at top MNCs and start-ups through by putting your best foot forward in our placement drives.

    Successfully Placed
    Hours Spent
    Recommendations Given
    by Hiring Partners
    Projects Completed
    by Students
    Still not sure what you will learn?
    Mentoring from Leading Experts
    Mentoring from Leading Experts
    Ankit Jain
    Data Scientist – Uber

    Past: Mentor – Springboard, Head of Data Science & Analytics – Runnr
    Education: B.Tech + M.Tech – IIT (Bombay), Master's in Financial Engineering – UC Berkeley

    Sumit Singh
    Senior Data Scientist – Subex

    Past: SE – Infosys
    Education:PhD in Decision Science – IIM (Bangalore)

    Arjun Tewari
    Data Scientist - Applied Materials

    Past: Data Scientist - Visa Business Analytics
    Education:ISB (Hyderabad)

    Palash Goyal
    Senior Data Scientist - Quaero

    Past : Process Lead, Data Science Consultant - AXA, MakeMyTrip
    Education : Mathematics & Computing, IIT-Guwahati

    Upcoming Batches
    Payment Plans
    Upfront payment
    (Inclusive of all taxes)

    Start your upfront payment process
    Invest Now in a Data Analytics Career

    The field of data analysis is growing by leaps and bounds. Data management and analytics have become vital for the success of corporations and industries worldwide.

    Even though some professions may not require extensive usage of analytics, there are still many that require this skill on a regular basis. This is the key reason why there are many Data analytics courses in India. Analytics courses are now available as live virtual classes and self-paced courses. Our 12-18 week long course has several advantages like 400 total coding hours and experienced industry mentors. This is the biggest advantage for understanding real world use cases and scenarios and applying theory in practice. Acadgild also ensures that real-time projects and case study discussions are facilitated to enhance learning. Icing on the cake is the lifetime access to our e-learning dashboard!

    Growing Field:

    Data analytics services are expected to generate a revenue of $187 billion by 2019.

    Well-Paying Jobs:

    Data Analysts earn around Rs 481,586 per year on average.

    Demand for R

    It’s the highest-paid IT skill and 36% of analytics job postings have R as a mandatory skill requisite.

    Speak to Our Course Advisor If You Have Queries
    (+1) 888 884 8355
    Why Our Courses Rank Amongst the Best
    Loved by Users
    • 4.4/5 (200+ REVIEWS)
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    Why Our Courses Rank Amongst the Best
    Loved by Users
    • 4.4/5 (200+ REVIEWS)
    • 4.3/5 (150+ REVIEWS)
    • 4.3/5 (150+ REVIEWS)
    Our Students Work With
    Transform your career with our courses
    The Acadgild Experience
    • Live sessions Expert Mentors conduct live sessions throughout the course Master technology through intensive online sessions
    • 24x7 Support 24x7 Coding Support Our support team will be there for you around-the-clock to help you with doubts.
    • Job Assistance 100% Job Placement Assistance Our team will guide you to your dream job
    Our Course in Comparison
    • Features
    • Duration
    • Live Sessions
    • Coding Assignments
    • Projects
    • Self Paced
    • Gamified Dashboard
    • Lifelong Access to Dashboard
    • 24*7 Technical Support
    • Portfolio Development
    • Fees
    • 18 Weeks
    • 72 Hours
    • NA
    • 5 +
    • 999
    • 5-8 Weeks
    • NA
    • NA
    • NA
    • 3,150

    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.

    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.

    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.

    Basic knowledge of math and statistics.

    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.

    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.

    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.

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

    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.

    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.

    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.

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

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

    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 - https://acadgild.com/blog/.

    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.

    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 [email protected]
    The details of the Refer and Earn policy can be found at https://acadgild.com/refer-and-earn.

    To request a refund, write to us at [email protected] 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.

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

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