What you'll learn

Definition of Data Science

Data Collection & Pre-processing

Statistics

Predictive Modelling

Requirements

None

Description

Data science is a multidisciplinary field that uses a combination of techniques, algorithms, processes, and systems to extract meaningful insights and knowledge from structured and unstructured data. Data science is of significant importance in today's world due to its transformative impact on various aspects of business, research, and decision-making. It incorporates elements of statistics, computer science, domain expertise, and data analysis to analyse and interpret complex data. Data science enables organizations to make informed decisions based on data analysis rather than relying solely on intuition or experience. This leads to more accurate and effective decision-making processes. During this course, students will learn the entire process of developing a data science project. During this course, students will learn the nuances of Data science, data collection, data cleaning, data visualization, Significance of statistics and Machine learning etc. We will be using r programming language to develop data pipelines. R is a programming language and environment specifically designed for statistical computing and graphics. It is open-source and widely used by statisticians, data scientists, researchers, and analysts for data analysis, statistical modelling, and visualization. R has a rich ecosystem of packages and libraries that extend its functionality. These packages cover a wide range of domains, from machine learning and data manipulation to bioinformatics and finance. So, let’s buckle up!!!