Data Analysis with R
Master data analysis techniques using R, from data wrangling to model evaluation and optimization.Data Analysis with R
Master data analysis techniques using R, from data wrangling to model evaluation and optimization.Data Analysis with R
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full IBM Data Analytics with Excel and R Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.7
(285 ratings)
27,160 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 3 more
Powered by
What you'll learn
Process and prepare data for analysis using R
Conduct comprehensive exploratory data analysis
Develop and evaluate predictive models
Implement various regression techniques
Optimize model performance through regularization
Create practical data analysis solutions
Skills you'll gain
This course includes:
1.9 Hours PreRecorded video
11 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Closed caption
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 6 modules in this course
This comprehensive course teaches practical data analysis using R programming. Students learn the complete data analysis workflow, from data preprocessing to model evaluation. The curriculum covers essential topics including data wrangling, exploratory data analysis, statistical analysis, and model development. Through hands-on labs analyzing airline performance data, learners develop skills in handling missing values, data normalization, regression analysis, and model optimization using techniques like regularization and grid search.
Introduction to Data Analysis with R
Module 1 · 2 Hours to complete
Data Wrangling
Module 2 · 2 Hours to complete
Exploratory Data Analysis
Module 3 · 2 Hours to complete
Model Development in R
Module 4 · 2 Hours to complete
Model Evaluation
Module 5 · 2 Hours to complete
Project
Module 6 · 5 Hours to complete
Fee Structure
Instructors
Program Director at IBM, Champion for Open Source Data & AI and Inclusivity
Gabriela de Queiroz is a Program Director at IBM, leading a team of developers focused on Data & AI Open Source projects. She is dedicated to democratizing AI, building tools, and launching innovative open-source initiatives. Gabriela is passionate about making data science accessible to all and is actively involved with several organizations to promote an inclusive and diverse tech community.
Innovator in Data Science and Machine Learning
Yiwen Li is a dynamic Software Engineer at IBM, where she excels as a developer advocate, data scientist, and product manager. With approximately three years of experience in the tech industry, she focuses on designing and developing data science solutions and machine learning models to address real-world challenges. Yiwen is an active speaker, having delivered engaging talks at prominent conferences such as JupyterCon, PyCon, and Global AI on Tour 2020, attracting hundreds of attendees. Her commitment to advancing the field of data science is evident through her contributions to educational platforms, where she shares her expertise in various courses related to data analysis and visualization. Passionate about bridging the gap between technology and practical application, Yiwen continues to make a significant impact in the realm of artificial intelligence and data-driven decision-making.
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
4.7 course rating
285 ratings
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.