Meet the Three-Time Nanodegree Graduate Using Deep Learning to Explore an Ancient Turkish Art

In a continuation of celebrating this year’s Women’s History Month, we would like to introduce Ayşin Taşdelen, an artificial intelligence professional and three-time Nanodegree program graduate. She has let her curiosity and desire for new skills lead her through three Nanodegree programs, new jobs, and side projects.

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We recently had a chance to speak with Ayşin to hear about her motivations and interest in pursuing cutting-edge technologies.

You studied mathematics during your university years and then became a programmer, what were some of your initial career goals?

I really enjoyed my university studies, so much so, that I initially looked into becoming a full-time researcher. Leaving academia was a tough decision, I loved learning but also knew that starting a traditional career would help me financially. I decided to go the career route and follow my interest in computer science. My initial career goal was to land a job and improve my programming skills.

As your career has developed, how have you satiated your desire to learn?

Over the years, I have tried to keep up with industry articles and books about the latest computer and tech trends. As the internet surged, I started using online library subscriptions and video learning paths. Reading and watching videos were great, but they only get you so far; I never felt like I was learning enough about a subject or concept, until, Udacity.

How were you introduced to Udacity and how did you choose your first Nanodegree program, Machine Learning?

I had spent eight years working as a software engineer, was in the midst of completing a master’s degree in Business Information Systems, and was setting myself up to be a manager. Up until this point, I had read about artificial intelligence, autonomous systems, machine learning, all of this advanced stuff, but thought that those industries and concepts were out of reach, my future was in IT management.

All of this changed when I read a blog post about TensorFlow by a highly regarded author who was working on a project that predicted butterfly breeds based on images (I also take butterfly photos!). I was amazed by the models and predictions the engineer could create. This is when I started to search for online opportunities to learn more about deep learning. That’s when I found Udacity.

While browsing through Nanodegree programs I saw a familiar name, Peter Norvig, involved with the Artificial Intelligence Nanodegree program. Previously, I had listened to a number of his lectures and was amazed by his teaching. Without a second thought, I applied to the AIND program—and got rejected.

I decided to finish out my master’s degree over the next six months and take another look at Nanodegree programs when I had more time and could select a foundation program that would lead to the AI program. Six months later, I graduated with my master’s degree and enrolled in the Machine Learning Engineer Nanodegree program.

I’m working on a Deep Learning Classical Art project … We’re using deep learning to collect and explore patterns in ancient Turkish art genres; collecting data about particular genres and classifying them by artist.

How was the experience? Did you encounter challenges?

I found the content to be so clear and concise. Concepts that previously seemed complex were broken down and made easy to understand. Watching videos and then completing projects associated with the content, filled the gaps I had noticed in my previous online learning efforts when I felt as though I wasn’t absorbing any skills.

The projects were challenging; I found that if I didn’t focus on the requirements exactly, I would spend time going back and fixing things. At one point, I submitted a project four times, but I stayed dedicated and pushed myself to keep going. Once I figured out how to focus on the project requirements, I was able to navigate through lessons more quickly. When I completed the Machine Learning program, I immediately enrolled in another.

In addition to the Machine Learning Nanodegree program, you’ve gone on to complete two more Nanodegree programs—what motivates you to keep learning?

All of these technologies are extremely exciting! I am constantly impressed by the scientists who are changing the world with their discoveries. Artificial intelligence, I believe has the most opportunity to bring change for all of us. As a programmer, I’ve always thought, much like every programmer, that my utmost mission is in moving frontiers to the next level, and AI is the way to do that. With the machine learning program, I created a foundation; with the Artificial Intelligence Nanodegree program, I solidified my passion and gained the skills to apply AI principles; and with the Flying Car and Autonomous Flight Engineer Nanodegree program, I’ve learned how AI can be applied to the 3D world.

am working alongside industry experts; three aeronautics Ph.D. students and the first three alumni to complete the Flying Car Nanodegree program—one of whom is myself!

You recently landed a new software engineering role that utilizes deep learning; did your Udacity learnings impact your ability to land this recent role?

Yes! I was recruited for an Android Developer role, but in the interview, they mentioned they were working to incorporate facial recognition software and computer vision into their products. The company manufactures gates for properties, and they’re working to make something as simple as an entryway, smarter.

I shared more on my Udacity studies, my interest in AI and computer vision, and they were intrigued. I accepted their offer as a Mobile App Developer and worked on that team for a short period, but recently, I started working on a computer vision project. Additionally, I am leading an effort that involves applying deep learning methods to one of our other initiatives.

Beyond work, do you use your new skills on any side projects?

I participated in the Alpha Pilot challenge organized by Lockheed Martin, which is the first AI and drone racing competition! I am so excited about this competition. Our team is working to pass the first stage and hopefully see our drone race against other teams. The opportunity to work on this team is particularly awesome; I had seen a video from similar groups on LinkedIn and thought “What the heck to do I know? I could never participate in this challenge.”

When I saw Alberto Naranjo Galet, a fellow Udacity Alumni, announce that he was looking for teammates to join the Velocity Vector team to enter the competition, I went for it! It’s an incredible experience. I’m working with people like Nuno Marques, a PX4 contributor and a leader in the drone community. I am working alongside industry experts; three aeronautics Ph.D. students and the first three alumni to complete the Flying Car Nanodegree program—one of whom is myself!

I’m also excited about working on a Deep Learning Classical Art project with a professor, Şebnem Özdemir, who invited me to participate based on my skills gained through Udacity. We’re using deep learning to collect and explore patterns in ancient Turkish art genres; collecting data about particular genres and classifying them by artist. We’re focused on one art form, Ebru, which I’ve always loved but never had the time or finances to pursue classes in during university.

My university is located in the old city of Istanbul, where this art form is abundant and many masters teach courses about it. Through this project, I am able to study alongside masters and learn this unique art form. With this project, I am living three of my life goals:

  • Continue my journey to becoming an Ebru Master, through the master-apprenticeship program, lead by Yılmaz Eneş
  • Being a team lead
  • Working as a researcher

Without the skills I obtained through Udacity and the professor running this project, I would never have had this opportunity.

You have accomplished so much! What’s next?

I don’t think I’ve accomplished so much yet! I feel like I triggered the start of a lifelong journey by learning at Udacity, and have so far had the chance to apply what I learned both in industry and academia.

Today, we’re told to have certain expectations about who we are and what we can become; there are so many prerequisites and rules. But this is frankly, not true. I thought I wasn’t able to do so many things until I just tried. I went from a Software Engineer to a Deep Learning and Computer Vision Engineer, who is working on a drone team and advancing the research of classical art. Anything is possible!

My dream is to spend the rest of my life working on new discoveries in AI and computer vision, to find ways to make the world a better place. I hope I can leave something behind or at least contribute to an advancement in tech which the rest of the world can benefit from. This is what I’ll be working towards each and every day.

With a blossoming career and prioritizing always building your skills, how would you inspire others to continue their own learning journey?

When I first started my software engineering career there was no one for me to talk for guidance or friends from college with similar experiences. I’m trying to share my experience and knowledge with others, something I would have wanted so badly back then.

Practical Machine Learning with TensorFlow 2.0 Alpha

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In 2016, Udacity released the very first free course on TensorFlow in collaboration with Google. Since then, over 400,000 students have enrolled in the course and joined the AI revolution. We’re excited to release an all-new version of this free course featuring the just-announced alpha release of TensorFlow 2.0: Intro to TensorFlow for Deep Learning. This update makes AI even more accessible to everyone, and we’ve again worked directly with the deep learning experts at Google to ensure you’re learning the very latest skills to utilize TensorFlow.

Google and Udacity Intro to TensorFlow for Deep Learning course

This free course is a practical approach to deep learning for software developers. Our goal is to get you building state-of-the-art AI applications as fast as possible, without requiring a background in math. If you can code, you can build AI with TensorFlow. You’ll get hands-on experience using TensorFlow to implement state-of-the-art image classifiers and other deep learning models. You’ll also learn how to deploy your models to various environments including browsers, phones, and the cloud.

Machine Learning for Everyone

The alpha release of TensorFlow 2.0 is a big milestone for the product. TensorFlow has matured into an entire end-to-end platform. In this alpha release, TensorFlow has been redesigned with a focus on simplicity, developer productivity, and ease of use. This release integrates Keras more tightly into the rest of the TensorFlow platform so that it’s easier for developers new to machine learning to get started with TensorFlow. Along with standardizing around Keras as the main API, other deprecated and redundant APIs have been removed to reduce complexity in the framework. A general release candidate will be available later in Q2 2019.

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The Race to a Machine Learning Career

This Udacity Nanodegree program graduate enacted a full-scale career change to become a Machine Learning Engineer.

Robin Stringer - Machine Learning Engineer - Udacity

Meet Robin Stringer. Robin worked as a journalist, a translator, and a marathon race guide for visually-impaired athletes, before a conversation about coding caused him to reevaluate his long-term career plans.

While he was working for a para-athletics non-profit in New York, he began learning Python online, and in the course of doing so discovered Udacity’s programs. He moved to Seattle and took the opportunity to pursue his coding studies full-time, with the goal of pulling off an audacious career change. After studying some of Udacity’s free courses, he started the Self-Driving Car Engineer Nanodegree program and got his first taste of machine learning. After a lot of work, he successfully landed a full-time role as a machine learning engineer.

We chatted with Robin to learn how he made his career change happen.

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Amazon SageMaker Comes to Udacity’s Deep Learning Nanodegree Program Classroom

We talk with Dan Romuald Mbanga, Global Lead of Business Development for Amazon AI, about teaching students to use SageMaker for training and deploying deep learning models.

Amazon - AWS - SageMaker - Udacity - Deep Learning

Deep Learning is one of the most exciting technology fields in the world today, and because Udacity’s learning platform is built to allow for maximum adaptability, our Deep Learning Nanodegree program is one of our most dynamic and future-facing programs right now, as we continue to respond to advances in the field by augmenting and enhancing our curriculum.

We are very excited to share details about the latest additions to our program curriculum, which include new content and projects focused on PyTorch and SageMaker. In a recent post by Cezanne Camacho, Curriculum Lead for Udacity’s School of Artificial Intelligence, we discussed new PyTorch content, and today, we’re going to explore how we’ll be teaching students to use SageMaker for training and deploying deep learning models.

To integrate the incredible new content, we teamed up with AWS and the SageMaker team, and in the updated program, students will train and deploy a sentiment analysis model on SageMaker, then connect it to a front end through an API using other AWS services. After deploying a model, students will also learn how to update their model to account for changes in the underlying data used to train their model—an especially valuable skill in industries that continuously collect user data.

To provide a closer look into the world of SageMaker, we spoke recently with Dan Romuald Mbanga, Global Lead of Business Development for Amazon AI, and a leader of business and technical initiatives for Amazon AI platforms.

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Introducing the PyTorch Scholarship Challenge from Facebook

Earn a scholarship from Facebook and Udacity, and learn how to build, train, and deploy state-of-the-art deep learning models with PyTorch. Apply today!

PyTorch Scholarship Challenge from Facebook - Udacity

Today, we’re pleased to share details of our newest offering to rapidly expand students’ machine learning skills —the PyTorch Scholarship Challenge from Facebook.

PyTorch is an open source deep learning framework that’s quickly become popular with AI researchers for its ease of use, clean Pythonic API, and flexibility. With the preview release of PyTorch 1.0, developers can now seamlessly move from exploration to production deployment using a single, unified framework.

This new scholarship program, announced today at the PyTorch Developer Conference, offers participants the opportunity to acquire cutting-edge skills in deep learning using PyTorch, and earn a full scholarship to Udacity’s Deep Learning Nanodegree program.

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Gil Akos, and his Nanodegree-powered path to co-founding Astra

Gil Akos knew the idea was a good one. He knew the product was something the world needed. But he didn’t have the skills yet to make it a reality. Four Nanodegree programs later, and Astra is live!

Astra - Udacity - Gil Akos

Gil Akos had an incredible idea for a new app. He wanted to empower individuals to make better decisions about their money through the power of technology. Gil believed that through smart financial modeling, based on deep learning, he could give people the power to make smarter moves with their money.  

There was just one problem. Gil’s background was in architecture, not artificial intelligence. While his self-taught programming experience could get him so far, he lacked the skills to turn his app into reality. So Gil set out to master the skills and tools he needed. He found Udacity, and enrolled in the Machine Learning Engineer Nanodegree program. Now, two years later, his new iOS app—Astra—has officially launched, and Gil has graduated from four (and a half!) Nanodegree programs that he took to learn the skills he needed to bring his app idea to life.

We spoke to Gil to hear about his story.

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Enter the $450,000 AI Challenger Global AI Contest Today!

The 2018 AI Challenger Global AI Contest is being co-organized by Sinovation Ventures—along with Sougo, Meituan-Dianping, and Meitu—and it features 10+ brand-new datasets, and a $450,000 USD prize.

Udacity - Sinovation - AI Challenger - 2018

In September of 2017, as an exclusive global education partner, Udacity had the pleasure of announcing details of a new AI competition and open data initiative organized by Sinovation Ventures. The event was entitled the AI Challenger Global AI Contest, and as Udacity COO Clarissa Chen noted in her contest announcement, “Artificial Intelligence has hit fever pitch in China. From cutting-edge tech powerhouses to established large corporations, everyone is setting up new AI Labs, hiring new talent, and announcing new platforms. “AI First” is the order of the day in China, and the excitement around this transformational technology is incredible.”

Success in 2017

The energy around AI across China was indeed incredible, and the subsequent success of the competition was clear evidence that it had been a perfect time to launch this kind of effort. Approximately 9000 teams from more than 60 different countries participated in the AI Challenger Global AI Contest, in 2017, and as reported by China Daily at the conclusion of the competition:

“AI Challenger released over 300,000 image-based as well as over 10 million language-based data entries to talents working on new technologies that will help AI applications ‘see’ and ‘read’ our world better.”

The 2018 AI Challenger Global AI Contest

China continues to represent a remarkable nexus for global AI innovation, and the 2018 AI Challenger Global AI Contest returns bigger, broader, and with more data than ever. As with last year, Udacity is especially pleased to be an exclusive global education partner, and we are excited to extend our ongoing collaboration with Sinovation Ventures to include new courses developed specifically to support contest entrants.

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