Associate Lecturer
2 weeks ago
Big Data and Machine Learning play a role in enabling policymakers to address important social and economic problems. Therefore, it is essential that data users and consumers can identify high quality data and understand the implications of poor data analysis.
In this course, students will explore how big data and machine learning are being used in economics and social science research. This course provides a practical, skills-based approach. Students will be guided through the process and pitfalls of using and interpreting results based on big data from project inception to final data analysis. Practical skills will be developed through the completion of weekly data analysis tasks and coding exercises.
Topics covered include: poverty and disadvantage, education, gender disparities, Covid-19 impacts, and social-policy evaluations. In the context of these topics, the course will also provide an introduction to basic methods in data science, including machine learning for prediction, causal inference (econometric approaches and machine learning embellishments), and heterogeneous treatment effects.
Job Requirement- Relevant bachelor’s or master’s degree with 5 years of work experienceAt least 2 years of relevant teaching experience at the tertiary level is preferred- Must be available to conduct a weekly 3-hour lecture for a period of 9 weeks- Must be available to teach classes during the day between 8.30AM and 6.30PM
- Additional Job Description
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Associate Lecturer
5 days ago
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Associate Lecturer
5 days ago
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