Adventures in Data Science: Progress

While brushing up on the algebra skills required for this Machine Learning course, I finished  "Logic and Computational Thinking" from Microsoft on EdEx.

I really enjoyed this course and so chose to go a little deeper with the IBM Data Science Professional Certificate, on Coursera.

The certificate consists of 9 courses, (I'm currently on #8) and so far I've learnt a lot about programming in python, data science methodology, SQL, databases, regression analysis, model evaluation and machine learning algorithms. The 7th course was "Data Visualisation with Python" and among other things I was able to turn raw data on 2016 crime rates in San Francisco into the Chloropleth Map below; so satisfying!
You can see the code for the data analysis and map creation on my Github here.

Raw crime data

Chloropleth map showing crime rates in San Francisco in 2016

Learning about data science and programming online has been the perfect mental stimulant for me while I negotiate the joyous yet tiring demands of being a new parent. The way the courses operate, I'm able to watch lectures and complete labs during naps, and complete longer assignments on the weekend. Having a tangible sense of progress and achievement in a new field has been really valuable to my sense of self, especially on the days when baby care seems all consuming.

Course certificate for Data Visualisation with Python

Once I finish this certificate, I think I'll focus on machine learning and a deep dive into python programming, so watch this space. If you're also getting into data science I would love to hear about what you're learning, the platforms you're using and what your goals are.

Back to basics.

As I suspected, I totally need to go back and brush up on my algebra skills in order to get the most out of the Machine Learning course.

Many data science sources online recommends Khan Academy as a wonderful (and free) way of learning the basics required for the course, so that's where I will start.

Wish me luck!

Baby Steps: starting out in Data Science

Hello!

I am 38 weeks and 3 days pregnant today, and have been on maternity leave for two and a half blissful weeks. I've taken 12 months maternity leave from my role as a Territory Manager in technical sales, and want to undertake some self-guided learning during this time, so that I can continue to grow professionally, whilst undergoing the huge life change that is having my first child.

In May, I finished the course 'Foundations of Data Science: Computational Thinking With Python' through the University of Berkeley on EdEx and loved the challenge of it, so I've decided to continue focusing my learning in the field of data science.

With this intention, yesterday I signed up to 'Machine Learning' by Stanford University, on Coursera. This is an 11 week course, but it's kept open for 6 months, so even if the timing doesn't work out around a newborn, I can switch into another stream.

I should note at this stage that the Data Science course I did in May was the first time I'd really touched any maths since I finished University 5 years ago, so I may well need to take some more math classes to get where I need to be with this Machine Learning course.

I thought I'd start a blog as a record of my learning process, both to keep myself motivated and so that I'd have something to look back on; to track the highs and lows of my progress.

Thus begins Math, Machines and Milk- wish me luck!