Analytics Training and Certification Courses


Analytics is the science of extracting insights and patterns from data sets. It typically involves collecting, cleaning, organizing, analyzing, and visualizing data in order to gain insight for making better business decisions. With analytics, data scientists and analysts create models to understand complex problems and develop data- driven solutions. They also use statistics and predictive analytics to identify trends and build custom predictive models with algorithms to make better decisions. Skills that can be gained from studying analytics include :
1. Data Analysis and Visualization :
data analysis and visualization is essential for understanding the data and extracting insights from it. Skills include statistical modeling, linear regression, machine learning, etc. 2. Machine Learning :
the ability to use and create data models to understand and make predictions from data. Skills include supervised and unsupervised learning approaches, neural networks, deep learning, and natural language processing. 3. Programming and Software Development :
data analytics often require the use of specific programming languages and tools. Skills include Python, R, SQL, MATLAB, and Big Data technologies like Hadoop, Spark, and Hive. 4. Data Transformation :
understanding data and manipulating it so it can be used for analysis. Skills include data wrangling, data mining, and ETL (Extract, Transform, Load). 5. Data Science :
a skill set that combines the different disciplines of data analytics to solve real- world problems and build data- driven products. Skills include predictive modeling, demand forecasting, and clustering.

The 1-on-1 Advantage


Flexible Dates

  • • Choose Start Date
  • • Reschedule After Booking
  • • Weekend / Evening Option

4-Hour Sessions

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Sr NoCourses/CertificationsCourse ContentsDurationFee*
E: Exam Included.
1-on-1 training (private class) – convenient start time, flexible timings.

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Prerequisites for Analytics Training and Certification Courses

1. Strong mathematical and statistical background

2. Understanding of analytics tools such as SPSS, R, SAS, Python, Tableau, etc.

3. Knowledge of programming languages such as SQL, Java, etc.

4. Familiarity with machine learning and AI concepts

5. Knowledge of data visualization principles and techniques

6. Ability to analyze and interpret large data sets

7. Ability to communicate effectively with clients

8. Knowledge of project management and analytics implementation processes

9. Understanding of business principles and industry best practices


Ans - No, the published fee includes all applicable taxes.

Yes, course requiring practical include hands-on labs.
You can buy online from the page by clicking on "Buy Now". You can view alternate payment method on payment options page.
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Yes, we do offer corporate training More details
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Yes, we also offer weekend classes.
Yes, Koenig follows a BYOL(Bring Your Own Laptop) policy.
It is recommended but not mandatory. Being acquainted with the basic course material will enable you and the trainer to move at a desired pace during classes. You can access courseware for most vendors.
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You will receive the digital certificate post training completion via learning enhancement tool after registration.
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Dubai, London, Sydney, Singapore, New York, Delhi, Goa, Bangalore, Chennai, Gurugram.
Yes you can request your customer experience manager for the same.
Yes of course. 100% refund if training not upto your satisfaction.