Advanced Topics in Data Science

Learning Outcomes

By the end of the course students will be able to:

a) to apply advanced data science techniques to solve real-world problems especially with respect to areas of digital humanities, natural language processing and related industries.

b) understand Advanced Data Science Techniques.

c) students will gain the ability to comprehend and apply advanced statistical and machine learning techniques such as deep learning to solve complex data science problems. They will acquire skills in selecting appropriate techniques based on data characteristics and problem requirements.

d) implement Data Manipulation and Preprocessing.

e) be proficiency in handling large and complex datasets through advanced data manipulation techniques including data cleaning, feature engineering, and dimensionality reduction. These skills will be focused on text and multimodal datasets in line with the rest of the programme.

f) interpret and Visualize data.

Students will create sophisticated data visualizations using advanced tools and libraries.

They will demonstrate skills in interpreting and communicating insights derived from visualizations effectively to different stakeholders.

Design Practical Big Data Pipelines

Hands-on experience with big data technologies such as Apache Spark, Hadoop, and distributed computing frameworks.

Plan and Assess Data Science Methodologies in Real-world Scenarios