For the code explained in each lecture, you can find a GitHub link in the resources section.

Kids can make wonders; many surveys and stats prove that the age from 5-15 is the best time for anyone in their entire lifetime to store as much data into their brain as possible. But the very idea of introducing them to such complex topics like AI and ML can be extremely terrifying. But worry not, we are here to help you take your kids into the world of ML. Machine learning is definitely not as easy as teaching rhymes but we can make it fun. "Rome wasn't built in a day" and hence, make sure you don't dig deep into the topics like robots or automation.

I finished my Business degree on 2014, I decided to study the A.I.. I started machine learning and deep learning in 2014. I got it myself in my school journal. Anyway, I was doing my best to study whatever it looks cool. Because it was only two years and it is not good enough to achieve the good knowledge.

It's a good day to learn something new, don't you think? Let's take a break from our ML / DL articles today and breathe together. Wouldn't it be nice to have a scholarship with many goodies available to you as a machine learning engineer or researcher-developer? I will be sharing with you how I went through the steps for this scholarship and my own roadmap. If you are looking for ways to achieve an AWS ML scholarship, let's chat together. This scholarship program, along with the adventure of being a core member of the TensorFlow Turkey community, has been a scholarship program that I learned through my dear teacher Yusuf Sarıgoz.

Hello everyone, we have updated this article recently, as the offer we shared here earlier has been updated and extended until the end of year 2021 while the supplies last. So, please take a note. Also, we hope you are staying safe from COVID19 and mastering new skills while staying at home. Here's a great news for our learners: The tech giant, IBM is offering Data Science and Artificial Intelligence Programs on Coursera for free for first 30 days until 31st of December 2021 (Updated). Consider looking at this exclusive offer here.

Education should not be a privilege but a common good. It should be openly accessible to everyone, with as few barriers as possible; even more so for key technologies such as Machine Learning (ML) and Data Science (DS). Open Educational Resources (OER) are a crucial factor for greater educational equity. In this paper, we describe the specific requirements for OER in ML and DS and argue that it is especially important for these fields to make source files publicly available, leading to Open Source Educational Resources (OSER). We present our view on the collaborative development of OSER, the challenges this poses, and first steps towards their solutions. We outline how OSER can be used for blended learning scenarios and share our experiences in university education. Finally, we discuss additional challenges such as credit assignment or granting certificates.

As we all know, Covid-19 struck Wuhan on New Year's Eve in 2019, and the city embraced total lockdown. Soon, the rest of China and the world followed. But what many don't know is Chinese education never went into lockdown. Within less than three months, Beijing Normal University (BNU) started a new semester offering more than 3,000 online courses. BNU could do so only because of China's comprehensive education technology (EdTech) drive in the preceding years, as a blog post at the Oxford Internet Institute elaborates.

This course gives you an overview of Computer Vision, Machine Learning with AWS. In this course, you will learn how to build and train a computer vision model using the Apache MXNet and GluonCV toolkit. This course tells you about AWS services and frameworks including Amazon Rekognition, Amazon SageMaker, Amazon SageMaker GroundTruth, and Amazon SageMaker Neo, AWS Deep Learning AMIs via Amazon EC2, AWS Deep Learning Containers, and Apache MXNet on AWS. In the final project, you have to select the appropriate pre-trained GluonCV model, apply that model to your dataset, and visualize the output of your GluonCV model. Now, let's see the syllabus of the course-

When compared to all other programming language, python is extremely simple, easy to learn, interpret and implement. Due to this reason it became very popular and trending programming right now. The job demand for python programmers are high. Python engineers have some of the highest salaries in the industry. There are plenty of Python scientific packages for data visualization, machine learning, natural language processing, complex data analysis and more.

Hello guys, if you are interested in learning about Artificial Intelligence and how to build AI and looking for free online resources then you have come to the right place. Earlier, I have shared free Machine Learning and Free Data Science courses and in this article, I am going to share free Artificial Intelligence and deep learning courses for beginners. These free courses are created from Udemy, Coursera, edX, and Pluralsight and created by experts and trusted by thousands of people who wanted to learn Artificial Intelligence. Clicking on this article link shows that you are very interested to understand and learn more about artificial intelligence but wait! Learning artificial intelligence is not that easy and never will be.