Udemy – R Programming for Data Science- Practise 250 Exercises-Part2 2024-8

Description

R Programming for Data Science Course – Practice 250 Exercises – Part 2. If you’re ready to take your R programming skills to the next level, this course is the ultimate hands-on experience you’ve been waiting for. Designed for data enthusiasts, future data scientists, and R programmers, this course brings you 250 new challenges that will deepen your understanding of R programming, data analysis, and machine learning. Whether you continue from Part 1 or just start here, this course promises to engage, challenge, and improve your skills in real-world applications of R. Explore problem-solving scenarios, practice advanced techniques, and get ready to advance your career in data science!

What you will learn in the course R Programming for Data Science – Practice 250 Exercises – Part 2

• Build a solid foundation in R programming by solving a variety of exercises and reinforce key concepts such as data types, control structures, and functions.
• Get hands-on experience with popular R libraries such as dplyr, ggplot2, tidyverse, and caret to effectively manipulate and visualize data.
• Apply data manipulation techniques to clean, transform, and organize real-world data using R.
• Improve your data visualization skills by creating insightful, professional-quality graphs with ggplot2 and other visualization libraries.
• Strengthen your statistical analysis skills by performing descriptive statistics, hypothesis testing, and regression analysis in R.
• Explore the various datasets available in R and use them to train machine learning algorithms such as linear regression, classification, and clustering.
• Debug and optimize your R code by identifying common errors and applying best practices for efficient coding.
• Prepare for real-world data science challenges by solving exercises that reflect common tasks in data analysis and machine learning projects.

This course is suitable for people who

• Future Data Scientists: Those looking to build a strong foundation in R programming while solving real-world data science problems.
• Students and Academics: Students studying data science or related fields who want hands-on practice with R and its various libraries and datasets.
• Professionals in data-driven roles: People working in fields such as business analytics, finance, healthcare, or marketing who want to improve their data analysis skills using R.
• Self-learners and coding enthusiasts: Those interested in learning R programming through hands-on exercises and improving their coding skills on data science projects.

Specifications of the R Programming for Data Science course – Practice 250 Exercises – Part 2

• Publisher:  Udemy
• Lecturer:  Sheikh Jamil Ahmed
• Training level: beginner to advanced
• Training duration: 3 hours and 0 minutes
• Number of courses: 503

Headlines of the course on 2024/9

Prerequisites of the course R Programming for Data Science- Practice 250 Exercises-Part2

• Basic understanding of R programming: Familiarity with R syntax, variables, data types, and basic functions.
• Introduction to data structures in R: Knowledge of common data structures like vectors, data frames, and lists.
• Passion to become Data Scientist
• Internet connection and laptop

Course images

Sample video of the course

download link

Download file – 539 MB

File(s) password: www.downloadly.ir

File size

539 MB