WSQ Data Science Modelling Project (SF) (Synchronous and Asynchronous E-LEarning)
About This Course
The " Data Science Modelling Project” module serves as a pivotal opportunity for students enrolled in the "Professional Diploma in Data Science " to apply the knowledge and skills acquired in preceding course modules. The Capstone Project module extends this foundation, enabling students to refine their practical skills by engaging in real-world projects and addressing industry challenges.
This module immerses learners in the day-to-day operations of live industry projects, allowing them to apply technical skills in data analysis, machine learning model development, and the utilization of deep learning techniques. Through hands-on experience with industry-standard tools, collaboration with professionals, and project management, students gain a comprehensive understanding of the data science lifecycle. The practical experience obtained not only enhances technical proficiency but also cultivates critical thinking, problem-solving, and communication skills within a professional context.
Ultimately, the Data Science Modelling Project module positions students as well-rounded data science and AI professionals, providing a competitive edge in the job market. Bridging the gap between theory and practice, learners showcase their ability to solve real-world problems and deliver tangible results. The acquired hands-on experience establishes a robust foundation for future careers, enabling graduates to contribute effectively to the industry and make a positive impact in the dynamic field of data science and AI.
What You'll Learn
The course duration is 130.5
The project tasks are
1. Develop a fraud detection model.
2. Provision and configure Azure ML services for fraud detection.
3. Perform sentiment analysis on customer reviews.
4. Enhance customer engagement and satisfaction.
5. Utilize Azure AI Language services for text insights.
6. Implement an Optical Character Recognition (OCR) system to extract text from handwritten documents.
7. Design and implement an FAQ chatbot.
8. Create a knowledge base for common queries.
9. Design, and test the chatbot to answer customer queries.
10. Deploy the question-answering chatbot.
Entry Requirements
Academic Qualification: Minimum 1 credit in O Level or its equivalent
Experience: Minimum 1-year experience in any business process