Understanding Data Analysis Using R

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Understanding Data Analysis Using R

Why This is needed Course & Target Audience:  In today’s data-driven world, the ability to analyze and interpret data is crucial for making informed decisions in any field. R is one of the most widely-used tools for statistical computing, offering powerful capabilities for data analysis, visualization, and predictive modeling. This course is needed because of Growing Demand for Data Analysis Skills, Hands-on Learning with a Leading Tool, Increased Analytical Capabilities and Industry Relevance. The target audience are Aspiring Data Scientists and Analysts, Researchers and Academics, Business Professionals and Managers, Students in STEM Fields and Professionals in Public Health, Social Sciences, and Economics.

  • Course Objectives: 

  • Course outcomes:

  • Master Data Import and Cleaning Techniques

  • Proficiency in Data Cleaning and Manipulation

  • Conduct Exploratory Data Analysis (EDA)

  • Strong Analytical Skills in Statistics and Modeling

  • Apply Statistical and Predictive Modeling

  • Advanced Data Visualization Abilities

  • Create Effective Data Visualizations and Reports

  • Experience with Reporting and Automation

    • Course Duration & mode of Delivery:

    This course will be delivered online over a period of 6 weeks, providing flexibility for learners to engage with the content at their own pace while still benefiting from structured learning. Each week, participants will access a combination of pre-recorded video lectures, interactive assignments, and discussion forums

    CORHOT COURSE TRAINING DATES: 24thMarch,  2nd June,   4rd November. 
    The course will be delivered by Eight Learning Virtual Platform https://8learning.org 
    Fees 200 USD

    Facilitator Profile:

    Dr. Hellen Namawejje ​

    The course will be facilitated by a team of three experts who are experienced lecturers of Makerere University with Ph.D. in Mathematics (Epidemiology). The team is led by Dr. Hellen Namawejje (namawejje-hellen-8b6a4042) a lecturer in the Department of Statistical Methods and Actuarial Science at Makerere University. she has been a part of the university’s Biometrics and Applied Statistics team and also specializes in designing and evaluating randomized controlled trials (RCTs), conducting impact evaluations, and assessing the effectiveness of health interventions using advanced statistical methods.

    Dr. Hellen together with Dr. Susan B. Tumwebaze and Thomas L. Odong (Ph.D) bring extensive experience in data analysis, statistical modelling, and programming in R to the course. With strong backgrounds in data science, research, and analytics, they offer practical knowledge and industry insights to help learners apply R effectively.
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