Journey to Data Science: From Guinea Pig to Professional
Delve into a captivating narrative of transitioning from a guinea pig at Brookes to a promising career in Data Science. Discover the driving force behind pursuing a master's, the enriching coursework experiences, and the allure of machine learning modules. Uncover the significance of distributed systems and the pivotal role they play in today's data landscape. This insightful journey encapsulates the essence of perseverance and passion in carving a path towards becoming a Data Scientist.
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Presentation Transcript
A brief History of (my) Time as a guinea pig at Brookes - and how it got me a job Julia Clark
Courtesy of Pinterest
What I will do My rationale for doing the course Recent highlights How it got me a job What I do / will be doing
Why this course? I wanted to do a masters in Data Science (or similar) Fairly local to where I live Flexible timescale Flexible location (can do remotely) The content very important I wanted a route to becoming a Data Scientist
Highlights of this year From semesters 1 and 2 of 2018/19 Semester 2 still ongoing
Introduction to Machine Learning (semester 1) Advanced Machine Learning (semester 2) - I love machine learning - explained using maths Reinforces, extends, and underpins Pre-processing and dimensionality reduction Supervised learning classification Also unsupervised learning / semi-supervised Coursework - freedom to choose methods or write your own algorithm
Sept. 2018 P08822: Lecture 1 11 Example: A Google Data Centre
Introduction to Distributed Systems (semester 1) A collection of independent computers that appear to the users of the system as a single computer Transparency, reliability, scalability Hadoop, NoSQL Map-Reduce Service-oriented computing JavaScript + possibly other languages Mixture of group and solo working
Time Series Analysis Hooshang always nice logical structure, good notes Comfort zone Trend Seasonality Random Walk
How it got me a job I don t think I d have got the job without it The fact that I was doing the course helped Showing commitment to the subject Being exposed to a lot of the essential ideas and technologies But most of all
Regression, regression, regression Regression Modelling (year 1, semester 1) Advanced Statistical Modelling (year 1, semester 2) The bedrock of everything else Technical test at interview Actual questions related to the subject in the interview
What have I been doing Can t talk about the data and I only started in February Working mainly in R SQL querying with Impala Lots of data munging and exploring I don t have to use Excel - hooray
Next few weeks Meeting SMEs Regression (probably logistic) Machine learning Topic modelling Network graphs possibly DAGs
Finally It has been hard work alongside working, running a house etc But I have enjoyed the experience so far there is the small matter of the dissertation If you re thinking about doing the course, I would say go for it.
Appendix Anscombe s quartet some cartoons I didn t use Modules covered / to cover
Modules completed 2017/18 Data Science Foundations Statistical Programming Regression Modelling Statistics in Government Survey Fundamentals Advanced Statistical Modelling
Modules 2018/19 Introduction to Machine Learning Distributed Systems Advanced Machine Learning Time Series Analysis Data Visualisation
Still to do Data Mining I hope Dissertation worth 1/3 of the total marks
