DEV Community: shahana khundmir

Gaining experience without a job

shahana khundmir — Fri, 19 Mar 2021 21:46:10 +0000

Once I felt that I was at a reasonable level of competence in Python I began applying for jobs, but every job wanted experience and there was no experience without a having had a job!

It was an ugly cycle that was difficult to get out of. So how can you make yourself employable without the elusive 'experience'.

Record your progress

The best piece of advice I was given is to use GitHub to showcase your work and I wish I had used it more and also more constructively. A well laid out GitHub account with regular code commits can be an amazing way to show what you have done and can do.

I created a GitHub account and uploaded the coding tasks set in my Udemy courses. Slowly I was able to build a picture of my skills, which was useful for me to see as well as for any prospective employers.

Practice

Coding is like Math, it just takes practice. So it's important to find projects to work on, the more meaningful they are the more you will enjoy and learn from them.

Codewars, Codility and HackerRank are all excellent platforms to practice coding in a variety of languages. They provide coding tasks to solve which are available at different levels of complexity so you can build your skill set.

It can be difficult to think of 'what' projects to do. For data analysis Kaggle is a treasure trove of ideas to work on and has pointers to lots of useful datasets. You can attempt to replicate analysis workbooks that you see on the site or submit your own work to Kaggle. Commit your work to GitHub at the same time as it maintains a picture of your journey.

Use opportunities to learn from others

Hackathons are a great way to practice your skills and network with like minded people. Pre-pandemic they were also a free food-fest and late night coding session.

I took part in the TrueCue Women in Data Hackathon in late 2020 which was conducted remotely with 200 participants from over 40 countries. This was my first experience of working with 'real' data analysts and gave me a unique opportunity to learn how data analysis worked in practice. It was a lot of fun and it felt meaningful to work on a project with an objective. Hackathons are also great places to network and build contacts in the industry.

7 best places to find Hackathons

LinkedIn, Twitter and other social media platforms are great places to link with others in the area you are interested in. During the pandemic there were an abundance of free courses online. It just takes a bit of research and time to find the right thing to focus on. Follow your interests, you can't possibly learn everything and follow everyone, it's counter productive. Find the people that push you to be inquisitive and make you look at your next steps. And take courses that fit into your long term plan or add wider understanding to the work that you are doing.

Volunteer

A friend mentioned a voluntary position on a data insight group who needed a secretariat, which I took on. While in this position I was in contact with data analysts in the charity sector and gained valuable insight into the way data was being used and the nuances and complexities that surrounded data usage.

Through this voluntary position I was approached by someone in the group to conduct an analysis of funding in the charity sector. It was an invaluable first job, for which I had already gained some background.

For Data Analysts DataKind is also an amazing place to volunteer on data analysis projects. It's valuable work and experience combined.

Python, Python, Python

shahana khundmir — Fri, 12 Mar 2021 20:40:19 +0000

A path back to coding

I had heard the buzz around Python, so when I decided to have a try at coding again I thought this would be a good place to start. Initially I wanted to see if I even had the knack for it still, so I did a short course on YouTube.

This course was 6️⃣ hours long but took considerably longer to go through. It's a really popular course and covered all the basic concepts. A cool extra was that it also touched on how Python is used in these three areas:

🌻 Automation
🌻 Machine Learning
🌻 Web Development

This gave me a taste of what the language had to offer and if I wanted to carry on learning. I really liked Python, it's an intuitive language to learn, has tons of support and some really powerful functionality. Most importantly it is being used in some emergent industries like Data Science, so it's a really good skill to have.

💾 A structured approach

Now that I had a good overview of Python, I wanted to learn it properly. I did this through Udemy. It's easy to find a good course on this platform, there are lots to choose from. They have reviews and you can watch intro videos to some of the session to get a feel of the delivery style. And best of all they always have offers and you can usually do a comprehensive course for as little as £20.

Complete Python Developer in 2021: Zero to Mastery

This is the course that I did and it was 30 hours long. It covered all the basic functionality and also extended features. Added to this were full sections on the above mentioned areas. All this is run alongside coding tasks so you get the best learning experience.
Be warned, it takes a long time to do the course properly. It took me several months, but at the end I really felt that I could use Python. The exercises are really important to work through properly, this is where you really grow and can start to feel your knowledge building.

While doing the course I set up a GitHub account to save my exercises, it helped me to build a picture of my skill set to showcase what I had learnt.

What next ..➡️

So I got to the end of this course and I thought 'What now?' this isn't enough to apply to a job, what type of jobs would I apply for? .. which direction do I take now ❓❓❓

So I decided I needed to choose an area to focus on and went with the area I had enjoyed the most, which was Data Analysis. My next step was another long Udemy course. This one was focused on Data Analysis and Data Science. It was in-depth and detailed, walking through the specific libraries and real life uses of Python in these areas. And the exercises built into a really good portfolio of my skills.

Python for Data Science and Machine Learning Bootcamp

By the time I completed this course I was 💫exhausted💫 but I also had a really good grasp of Python and how to use it to analyze data sets and produce visualizations, as well as a good understanding of Data Science modelling.

My Return to Tech

shahana khundmir — Fri, 12 Mar 2021 17:47:38 +0000

Computing graduate📚 Mum of five 💪 and Avid coder 📜

I was 12 and a family friend had immigrated and left behind their BBC Basic computer. We couldn't have afforded that computer, but that one event started me on my journey in development. I learnt to programme by breaking and fixing code, learning syntax along the way.

I coded pretty much for the next 10 years until my graduation. I met a few women along the way. But the shortage of women in tech didn't really dawn on me until I began to work and have a family.

My career began and ended as a Java Developer. It was 2001 and the industry was male dominated.👦👨👴👦👨👴👦👨👴👦👨👴👦👨
Everyone was a back-end developer and the technical work environment involved long hours, innovation and start-ups were the life blood of the industry.
I took a break in 2001 to have my eldest 2 children. 3 years later when I thought about returning the industry had moved on considerably and I lacked the confidence to take on this challenge.

After leaving my job as a developer I spent the next 15 years raising my kids, contracting as a project manager and running my own company for a few years. As the gap in my IT career grew bigger I came to accept that that part of my life was over and Tech was something I couldn't return to. But it always irked me that I had given up something that I loved😞

Fast forward to 2019 and my now 19 year old daughter dragged me to a Women in Tech evening at IBM. I didn't know this movement even existed and was so inspired by the talks I heard that evening that I was one of the last to leave✨ 🌟👧👩👵👧👩👵👧👩👵🌟✨

I enrolled on my first Python course soon after and loved it so much that I decided to give Returning to Tech a real shot!