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.
Overview
This course includes:
- 3 hours on-demand video
- Numerous downloadable resources
- Full lifetime access
- Certificate of completion
Skills You Will Gain
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.