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  1. On Air
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  3. Introduction to Data Analysis using R
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Introduction to Data Analysis using R

This course – with expert Pramod Gupta -- examines different approaches to a data analysis project, with a framework for organizing an analytical effort. Popular tools for data analysis, such as R and Python, are introduced to carry out analysis.

Pramod Gupta
Pramod Gupta
Data Science | core | 5 minutes | Apr 29 | 08:38 AM Eastern (USA)

Overview

3.6KSTUDENTS*
94.6%RECOMMEND*

This course includes:

  • 12+ hours of on-demand video
  • 9 modules
  • Core level
  • Direct access/chat with the instructor
  • 100% self-paced online
  • Many downloadable resources
  • Shareable certificate of completion
The course examines different approaches to a data analysis project, with a framework for organizing an analytical effort. Popular tools for data analysis, such as R and Python, are introduced to carry out analysis. The course covers how to obtain and manipulate the raw data for use, as well as the basic exploratory analysis and common data analytical techniques such as regression, simulation, estimation and forecasting. It includes several graphing and visualization tools to understand the data and to present findings and results. Overall goal of this class is to introduce participants to the discipline of data analysis/ data mining, a science of understanding and analyzing data. The class is designed to provide participants with the tools they need for solving real world problems using statistics and a better understanding of data analysis techniques. By the end of the course, you will learn a working framework to approach any data analysis project. You will be able to use R (or Python) to complete a large data analysis project, including a write-up with findings, insights and visuals. All tools used are open sourced. In this program, you will learn the practical expertise regarding data analysis. You will understand how it is the process of transforming data into useful information to support decision making. It is the foundation for data mining, business intelligence, and predictive analytics. This course presents the tools, techniques and common practices used in the industry, including how to obtain, manipulate, explore, model, simulate and present data. It will help you build the essential technical skills to perform as data analyst or data scientist, and to continue other course studies in the certificate program.  

Skills You Will Gain

Data Analysis
R
R Studio

Learning Outcomes (At the end of this program you will be able to)

  • Perform independent analysis of data
  • Understand use and navigate R Studio and R
  • Implement various algorithms for their needs and improve/modify existing algorithms/techniques for data analysis
  • Apply data manipulation techniques for greatest impact
  • Use advanced data manipulation tools in analysis
  • Implement techniques for data visualization
  • Understand how to use probability and estimation in data annaalysis
  • Use modelling and regression tools
  • Implement time series analysis
  • Present analysis and results in a clear and convincing manner

Prerequisites

  • Basic Python knowledge is assumed
  • Some software development experience (including languages, databases…)

Who Should Attend

  • Anyone who wants to learn about using Python to build, evaluate or deploy machine learning and Artificial Intelligent models.
  • Scientists, engineers, business analysts, research who explore and analyze data and wish to present their findings in well-formatted textual and graphical forms.
  • Anyone wishing to get hands-on experience building machine learning models.
  • Professionals, students and job-seekers interested in learning the fundamentals of machine learning and data mining and want to learn to build, evaluate or showcase machine learning applications in Python.
  • The course will be appealing mostly to people that need an introduction to numerical computing and visualization using Python environment and also for technical staff that want to enhance their Python programming skills on the specific topics. Anyone who is interested in using Python’s NumPy, Scipy and Matplotlib packages as prototyping tools would also benefit from the course.

Instructors

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*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
Pramod Gupta

Pramod Gupta

Dr. Pramod Gupta is a passionate data scientist and educator with over 20 years of experience in data mining, predictive analytics, and applied machine learning. He excels at transforming complex data into actionable insights and developing algorithms that solve real-world problems. His expertise lies in leveraging advanced statistical and predictive modeling techniques, utilizing tools such as Python, R, and SQL to deliver impactful, data-driven solutions.

Deeply committed to educating the next generation of data scientists and machine learning professionals, Dr. Gupta designs his courses with a strong emphasis on practical applications and solving real-world challenges. He ensures that his students not only grasp theoretical concepts but are also equipped to apply them effectively in their professional careers.

Driven by an enduring passion for learning and sharing knowledge, Dr. Gupta’s career is marked by numerous research publications and significant contributions across diverse industries, including bioinformatics, finance, and retail. He believes that teaching is a two-way exchange—where he gains valuable insights from his students just as much as he imparts knowledge—creating a dynamic and enriching learning environment.

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