Bachelor of Data Science and Analytics

Course Description

Data Science and Analytics is an interdisciplinary field that combines elements of statistics, computer science, and domain-specific knowledge to extract insights and knowledge from data. It involves collecting, cleaning, processing, analyzing, and visualizing large and complex data sets using various analytical and statistical tools and techniques.

Data Science and Analytics are used in many industries and fields, including business, healthcare, government, social media, sports, and more. It helps organizations make data-driven decisions, solve complex problems, and identify new opportunities.

Some of the key skills required for Data Science and Analytics include:

1. Data wrangling: Collecting, cleaning, and transforming data to make it usable for analysis.

2. Statistical analysis: Applying statistical methods to identify patterns and relationships in data.

3. Machine learning: Using algorithms and models to predict outcomes or classify data.

4. Data visualization: Creating charts and graphs to communicate insights and findings.

5. Programming: Knowledge of programming languages such as Python or R to manipulate data and build models.

Some of the popular tools and technologies used in Data Science and Analytics include Python, R, SQL, Hadoop, Spark, Tableau, and more. The field is constantly evolving, and professionals in this field need to keep up-to-date with the latest trends and technologies.