Celebrating Jolt - Introducing Ampair

WE ARE WATTX

By
Thomas
Vika

March 06, 2019


When we first started Jolt last autumn, we had no idea how it would work out. Now, a few months later, we closed the first round of mentoring with some really great results - and a new name. Jolt has evolved and has now become Ampair. We are open for applications now and will begin the second round of mentoring in just a few weeks with more than 4 times the number of mentors and mentees compared to the first round.

Before we take that next big step, we want to look back at the first round and some of its great achievements. During the three months project phase, mentees have been working hard on the projects of their choice being guided by the field experts - their mentors. They had an opportunity to present the outcomes of their efforts during the closing celebration that marked the end of the first phase. All the presentations were super interesting and left the audience impressed with how much can be achieved during such a short period!

As we understand that getting started in tech is not trivial, we wanted to offer a special form of recognition for the best and thus asked the audience to vote for three projects they found the most captivating. Today, we are presenting you with the winners - Maria, Laurie & Max who told us a little bit about their projects, the experiences they had and why they think mentoring can make all the difference when learning a new skill.


What motivated you to apply to our mentoring program and how did you find out about it?

Laurie: I’m new to programming and I wanted to get better at Java and SpringBoot. I started looking for a mentor, but it turned out to be really hard to find a mentor for Java in Berlin. I was going through meetups and Slack communities, but I didn’t find any, so when I finally found Jolt, it was a no brainer that I had to immediately apply for Blake as a mentor for backend engineering.

Max: At some point in my professional life, I realized that within the next 10 years my job might be replaced by machines and wanted to get ahead of it. I had only limited practice in programming so I started with an online beginners course for web development. However, with a full-time job, that’s really hard to do without having a clear goal or people that help along the way. So I started looking for a mentor.

Through my Berlin energy start-up networks, I first found VC/O, then WATTx, and discovered an interview with Fran on the WATTx website that I could relate to. She also changed her career path and went into development. I actually wanted to ask her directly to be my mentor but then, on the next day, Jolt was released and it turned out that Pedro was the perfect mentor for my smart home project idea.

Maria: I am currently studying NLP (natural language processing) and just had a really cool subject of machine learning. I thought I’d forget about all of the things I learned if I didn’t apply them right away. When I found Jolt through the slack channel from PyLadies, I applied for Kevin as my mentor right away.


Could you describe the project or solution you worked on during the program?

Max: In Germany, most of our energy consumption goes into heating, which causes a lot of CO2 emissions. As a tenant in an old Berlin building, I cannot do much about the heating system or the insulation of the house. So my project aimed at improving upon the user behavior. I built a smart home system that teaches me how to minimize my heating consumption without compromising comfort.

I had several questions (e.g. should I lower the temperature at night or keep it the same throughout?), but there are no simple answers. Also, each answer is not necessarily true for every apartment, as insulation is a big factor. I learned that in my case I can lower the temperature at night by a lot.

There are some very expensive smart home solutions tackling this, but I wanted to find a cheap system that everyone could apply.

myHEMS showcase Recording showing Max’s prototype in combination with the sensors he used for his proejct


Maria: I focused on emotion recognition from human speech, because I was generally interested in computer perception. I thought it would be interesting to apply machine learning to something more psychological, like recognizing emotions in your voice, regardless of the words said.

My main problem during project execution was the availability of data and its quality. In the end, having applied some data analysis techniques and experimenting with different machine learning models (e.g. SVM, Logistic Regression, sequential models), we yielded some results. Now the algorithm is able to distinguish between four emotional classes: anger, fear, excitement, and neutral speech.

waves Audio waves depicting typical sound profiles of the emotions angriness, fear, happiness, and a neutral baseline (top to bottom) as recorded by Maria


Laurie: When the program started, I was looking for a new apartment. While I was going through that process, I found it painful that I had to go to different websites, with each of them having a different UI, different experience, and also different listings. So I thought, why not build my own application that does two main things: 1) aggregate all data from websites such as ImmobilienScout24, or WG-Gesucht, etc. and 2) inform me whenever a new apartment matching my searching criteria - from any of those sites - comes up.

The backend is built on Java and SpingBoot, and I use the Slack API for the frontend.

SQgyOiKP5B Slack interface used as frontend for Laurie’s flat search engine & notification system


Can you summarize the one or two main things you learned?

Maria: There are many things I learned! Apart from all the technical things we used (scikit-learn, NumPy, Pandas, Bash etc.), Kevin, taught me how to set up realistic goals for myself. It was really nice to learn how to see the solutions that are affordable and achievable in a specific timeframe and get the right mindset for it.

Then, I also learned that the main problem in a Data Science project is the data, not the model and that working on a real problem is different from university projects sometimes.

Laurie: I learned a ton. To summarize: in terms of technical skills, I cannot even describe how much. I learned everything I wanted (Java and SpringBoot) and more. I learned how to architect an application, and how to decide on the right tools to achieve my goals. I also learned project management, including how to set realistic goals. In the beginning of the project, I panicked a bit when I thought I wasn’t progressing as much as I had hoped. But then I sat down with my mentor to go through what I have achieved, and what still needs to be done in the remaining time frame. This exercise made my remaining tasks look much more feasible and realistic, and helped me feel calmer approaching the program.

Max: On the tech side, I learned to program in Python and to build a fully working hard- and software system—not just some random algorithms like in my uni courses. Also, I’d stress the same point as Maria about data—the biggest challenge was to get the data in the right format and work with time series that are not aligned. Now I also understand the great importance of Data Scientists.

Reflecting on my personal development, I learned three key things—to be patient in the learning process, to ask the right questions, and to rely on help from others. And finally, I realised that I like working in development. That is exactly what I wanted to find out through the program.


In one sentence, how would you describe your experience going through this mentoring program?

Laurie: Life-changing. For me at least, because it is really incredible how much I’ve leveled up in just three months - in 12 weeks! You realize so much about what you can and cannot do.

Max: For me, it was like climbing a mountain. I cannot do it on my own if I don’t know the tools or have never done it before. With the help of my mentor and the community, I was able to learn climbing a huge mountain…

Laurie: …together…

Max: … and learning which tools are the best for each task.

Maria: There are many things and one sentence is certainly not enough to describe the experience. However, it comes down to doing what you love. If you think about it - that’s what participating in this program means for me.


How do you perceive the role of mentoring in tech?

Laurie: It’s incredibly important: mentorship is invaluable. For people that are just starting out, the journey can feel really lonely, and one can often feel stuck. Having a good mentor and community that supports you can change your perception of the whole situation - and make or break whether you want to continue in the field or not. That is also why one of my main goals from this program is that I hope I can take what I’ve learned to also help others in their programming journey.

Max: I think it’s very important to have a mentor. Some people think their boss could be their mentor, but I don’t think that’s possible. You need someone else that can answer your questions that you’re not in a hierarchical relationship with. Having a good mentor, and a community, helps to focus and to get on the right learning and career path. I hope I can be a mentor for others in the future, too.

Maria: They have said everything already. I just want to add that I think I am going to miss it. Mentoring and the whole experience is very important. You think you kind of know the approach, but mentors help you guide your thinking and creativity. They have so much experience and ask the right questions. You learn a lot from that.

Max: They’re also kind of role models.

Laurie: Exactly, that’s why I really appreciate them offering their time.

Maria: Yeah, it was very individual. Just following textbooks is not that easy and applicable.