Introduction to R for Data Analysis
Program Overview
This 10-week online course provides an intensive introduction to R programming for data analysis. Participants will acquire the technical knowledge and skills to extract valuable insights from large datasets, fostering their careers as data analysts. The course emphasizes the practical application of R in organizational settings, utilizing R techniques to analyze real-world datasets and communicate findings through powerful visualizations. Upon completion, participants will be well-equipped to pursue careers as data analysts in various sectors.
Program Outline
Introduction to R for Data Analysis (Short Course)
Degree Overview:
This 10-week online course offers an intensive introduction to the R programming language and its applications in data analysis. Participants will acquire the technical knowledge and skills to extract valuable insights from large datasets, fostering their careers as data analysts. The course delves into the fundamentals of R, including data structures, manipulation techniques, and statistical functions. Participants will learn to create and customize functions tailored to their specific analytical needs. Advanced topics such as sophisticated graphics, data mining algorithms, and statistical modeling are also covered, providing a comprehensive foundation for data analysis with R. The course emphasizes the practical application of R in organizational settings. Participants will utilize R techniques to analyze real-world datasets and communicate their findings through powerful visualizations. This practical approach empowers participants to leverage data analysis as a strategic tool for organizational planning and decision-making.
Outline:
The course curriculum is structured to provide a progressive learning experience, starting with the basics of R and gradually progressing to more advanced concepts and techniques.
- Data Structures: Participants will explore the fundamental data structures in R, including vectors, factors, matrices, lists, and data frames. They will learn to manipulate these structures effectively using various functions, including aggregative functions, indexing, and the apply() family.
- Graphics: Beyond basic plotting techniques like plot() and hist(), the course delves into advanced visualization tools like ggplot2(), Tableau, and Power BI. Participants will learn to leverage these tools for in-depth analysis and presentation of their findings.
- Statistics: With a focus on practical applications, participants will engage with key statistical concepts like descriptives, distributions, regressions, and correlation analysis. They will also cover more advanced topics like t-tests, ANOVA, and categorical data analysis. The course emphasizes the rigorous application of these techniques to solve real-world organizational problems.
- Programming: Participants will gain a solid understanding of procedural programming principles, including variables, control structures, and writing simple functions. They will then progress to building more sophisticated functions designed for efficient large-dataset manipulation.
- Data Loading, Cleaning, and Transformation: Participants will learn to import data from various sources, including Excel, SQL, XML, and the web. They will master SQL for effective data querying within R and explore techniques for data cleaning, transformation, merging, and sampling.
Assessment:
Continuous assessment is utilized throughout the course to monitor and enhance student learning.
- In-class exercises and assignments: Participants will engage in regular exercises and assignments to test and expand their knowledge of R concepts and techniques.
- Data Analysis Project: A continuous data analysis project serves as the primary assessment tool. Participants will use R techniques to analyze real-world data, deriving insights and communicating their findings through visualizations.
Teaching:
The course employs a blended learning approach, combining interactive lectures with hands-on practical exercises. This approach fosters a dynamic learning environment where participants can actively engage with the material and receive immediate feedback on their progress.
Faculty:
The course is led by experienced data science professionals with a deep understanding of R and its applications in various industries. This ensures that participants receive the most up-to-date and industry-relevant knowledge and skills.
Careers:
Upon completion of the course, participants will be well-equipped to pursue careers as data analysts in various sectors. They will be able to leverage their data analysis skills to extract valuable insights from large datasets and utilize those insights to inform strategic decision-making in their respective organizations.
Other:
The course is designed to be flexible and accessible, allowing participants to learn at their own pace and from the comfort of their own homes. It provides an excellent opportunity for individuals to upskill or refine their existing data analysis skills, enhancing their employability in the data-driven world.
City University of London
Overview:
City, University of London is a public research university located in London, England. It is known for its focus on business, practice, and the professions, offering a wide range of undergraduate and postgraduate programs. The university is renowned for its strong academic reputation and its commitment to providing students with a high-quality learning experience.
Services Offered:
City University of London provides a comprehensive range of services to its students, including:
Library Services:
Access to extensive library resources, including books, journals, databases, and online resources.Moodle:
An online learning platform for accessing course materials, submitting assignments, and communicating with instructors.Email:
A university-provided email account for official communication.Staff Directory:
A searchable directory of staff members and their contact information.Term Dates:
Information on the academic year and term dates.Room Booking:
A system for booking rooms on campus for meetings, events, and other purposes.Schools and Departments:
Information on the various schools and departments within the university.Student Life and Campus Experience:
City University of London offers a vibrant and diverse student experience, with a strong emphasis on:
London Experience:
The university's location in London provides students with access to a wide range of cultural, social, and professional opportunities.Sports:
A variety of sports clubs and facilities are available for students to participate in, both competitively and non-competitively.Social Activities and Groups:
Numerous student societies and groups cater to diverse interests, providing opportunities for social interaction and personal development.Student Wellbeing:
The university offers a range of support services to ensure students' health and wellbeing, including learning support, personal tutoring, and counseling.Career Development:
The university provides career guidance and support services to help students prepare for their future careers.Key Reasons to Study There:
Strong Academic Reputation:
City University of London is consistently ranked highly in national and international rankings.Focus on Business, Practice, and the Professions:
The university's programs are designed to provide students with the skills and knowledge they need to succeed in their chosen careers.Location in London:
The university's location in the heart of London provides students with access to a wealth of opportunities.Vibrant Student Life:
City University of London offers a diverse and engaging student experience.Excellent Career Support:
The university provides comprehensive career guidance and support services.Academic Programs:
City University of London offers a wide range of academic programs across various disciplines, including:
Business and Management:
Bayes Business School is renowned for its programs in finance, accounting, marketing, and entrepreneurship.Law:
The City Law School is a leading institution for legal education, offering programs in law, international law, and legal practice.Health and Psychological Sciences:
The School of Health & Psychological Sciences offers programs in nursing, midwifery, psychology, and other health-related fields.Science and Technology:
The School of Science & Technology offers programs in computer science, engineering, mathematics, and other STEM fields.Communication and Creativity:
The School of Communication & Creativity offers programs in journalism, media, performing arts, and language studies.Other:
Merger with St George's:
City University of London has merged with St George's, University of London, forming a new institution called City St George's, University of London.Awards and Accreditations:
The university has received numerous awards and accreditations for its teaching, research, and commitment to equality and diversity.Global City:
City University of London is a global institution with a strong international presence.University of London:
City University of London is a member of the University of London, a federation of 18 independent colleges and institutes.Entry Requirements:
EU Home Students:
- Applicants should hold a good honours degree (2:1 or above) or equivalent in a relevant subject such as statistics, mathematics, computer science, bioinformatics or a related field.
- Applicants with a lower second class honours degree (2:2) or equivalent may be considered if they have relevant work experience or other evidence of professional qualifications.
- A strong background in mathematics, statistics, and computer programming is required.
- Applicants should be familiar with the basic concepts of data analysis and statistical modeling.
International Overseas Students (Outside the EU):
- Applicants should hold a good honours degree (2:1 or above) or equivalent in a relevant subject such as statistics, mathematics, computer science, bioinformatics or a related field.
- Applicants with a lower second class honours degree (2:2) or equivalent may be considered if they have relevant work experience or other evidence of professional qualifications.
- A strong background in mathematics, statistics, and computer programming is required.
- Applicants should be familiar with the basic concepts of data analysis and statistical modeling.
- Applicants must also meet the University's English language requirements, which are:
- IELTS Academic: 7.0 overall with no less than 6.5 in any component.
- TOEFL iBT: 100 overall with no less than 24 in each section.
- Pearson PTE Academic: 70 overall with no less than 65 in any component.
- Cambridge English: Advanced (CAE) or Proficiency (CPE) with a minimum score of 185.
Additional Information:
- Applicants are encouraged to submit a personal statement outlining their academic and professional goals, as well as their reasons for wanting to study this program.
- Applicants may be required to attend an interview as part of the admissions process.
- The program is highly competitive, and meeting the entry requirements does not guarantee admission.
