Embark on a rewarding journey into the world of data analytics with our 5-day Data Analytics with R Specialization course. This comprehensive training is designed to equip you with in-depth knowledge and practical skills in using R, a powerful programming language for statistical analysis and data visualization. The course begins with the basics of R programming, ensuring a solid foundation even for beginners. As you progress, you will explore advanced data manipulation techniques and delve into the intricacies of data analysis. Our expert instructors will guide you through real-world scenarios, helping you understand how to apply these skills in a practical setting.
The second half of the course focuses on more complex aspects of data analytics, including predictive modeling and machine learning using R. You will learn to create compelling data visualizations, a crucial skill in interpreting and presenting data effectively. This course not only enhances your analytical capabilities but also prepares you to tackle real-world data challenges in various industries. Whether you're a professional looking to upskill, a student interested in data science, or an enthusiast eager to dive into data analytics, this course will set you on the path to mastering data analytics with R in just five days, opening doors to numerous career opportunities in the ever-growing field of data science.
All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.
Topic 1.1 Getting Started in R
Topic 1.2. Data Types
Topic 1.3. R Packages & Data I/O
Topic 1.4. Data Visualization
Topic 1.5. R Programming
Topic 1.6. Statistics Analysis with R
Topic 2.1 Data Preparation and Transformation
Topic 2.2 Data Summary
Topic 2.3 Quantitative Data Analysis
Topic 2.4 Qualitative Data Analysis
Topic 2.5 Data Visualization
Topic 3.1 Overview of Machine Learning
Topic 3.2 Regression
Topic 3.3 Classification
Topic 4.1 Clustering
Topic 4.2 Principal Component Analysis
Topic 4.3 Deep Learning
Topic 5.1: Introduction to Text Mining
Topic 5.2: Basic Text Functions
Topic 5.3: Importing Data
Topic 5.4: Tidytext Package
Topic 5.5: Word Frequencies & Relationships
Topic 5.6: Sentiment Analysis
Topic 5.7: Topic Modelling
Topic 5.8: Document Similarity & Classifier