Professional Certificate In Computer Science For Artificial Intelligence – Yes! I completed a course in Computer Science from the Massachusetts Institute of Technology – more famously MIT. Unfortunately, while visiting the campus in Cambridge, Massachusetts, USA, I found this course so good that I participated in a six-week online course, the MIT Professional Education program: “Data Science: Data to Insights”. It’s about solving complex problems with your data – as the teaser explains. The topic is becoming increasingly important today, as 90 percent of the world’s data has been created in recent years.
Wondering if you should take that course? So I thought it was only fair that I share some information with you. To get my point across, I’ll give you some personal background information about my IT career and background in artificial intelligence (AI).
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I have a degree in computer science and I have a Masters in Digital Media. When I studied, AI was not as popular a topic as it is now. However, it was my own opinion in my diploma in 2005. Unfortunately, I could only work for a short time as a programmer, and I could not do another discipline in AI. For about 10 years now, I have focused on IT consulting topics, especially IT-shoring, -sourcing and customer integration. I specifically chose this online course because I want to understand the possibilities and limitations of methods and techniques.
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Each module is accompanied by 10-20 videos (completing highly selective assessment) and anywhere between one and seven lessons. Students receive their certificate and CEU (1.3) only with the completion of all assessments.
To successfully complete the modules, the (assistant) teachers provide students with online courses, enhanced with animations and images. Participants can discuss a wide range of topics and questions in an online forum. Algorithms and ideas are often presented in business or real-life scenarios, such as Netflix or Facebook.
In the first module you will learn how to identify patterns and hidden structures in data. For example, you can learn how to build all your text on your computer based on certain topics. Or, if you want to find hidden communities in a network – called clustering – then you can do that.
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The focus is on bivariate and multivariate regression for the purpose of forecasting and factor analysis, followed by logistic and non-linear regression. You will learn how to solve forecasting problems with advanced data, including lasso, regression, regression models, exponential trees, random forests, and more.
Starting with the statistical methods of classification, hypothesis testing and its applications, including the detection of statistical anomalies, detection of fraud, spam, and other forms of abuse. For example, a binary number is classified as spam or spam. You will be introduced to neural networks, perceptron (an algorithm for learning binary numbers), deep learning and their limitations.
, teaches you how to find relevant information from large amounts of data. You will learn how Netflix recommends new movies to its users; how Amazon, Facebook or Spotify promote their users. You will learn different principles and algorithms for concepts, ranking, combinatorial analysis and personalization.
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Let you know what a website is. For example, how information or ideas are spread in a social network is related not only in a marketing way but how it can be used for other purposes, for example in wrong information. You will learn about algorithms for analyzing large networks and ways to model network processes.
I love the program because it opens the door to the impossible things in technology, things that have always changed and will continue to change our world in the years to come. The instructors teach at a high level and speaking for all of us who took the course – we can honestly say that we learned something new.
There will be a lecture (an hour and a half) by Victor Chernozhukov (http://web.mit.edu/~vchern/www/), a young professor with Russian/American heritage from the Department of Management. .
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His talent, (besides his great skills in regression and prediction), lies in his ability to deliver lectures through mathematical calculations alone. He reads formulas like news headlines! It’s not hard not to have a lot of respect for him. Having watched the video several times, I have an idea of its content. Internet is very helpful, especially YouTube videos about math. And that’s just the opposite there. Even in school, our teacher has only one definition of the subject, but now we can practice as much as we want and the subject is fixed.
When you can get past this difficult lecture, others are very happy, especially those in deep learning. It was so striking that I watched it twice. In deep learning, the programmer only teaches the system how to learn, and how to solve a problem. The system has a learning experience that searches and teaches itself – the program learns from past data.
For example, the website reads pictures of animals and the name of the animal in the test set. So, he himself learned how to recognize a dog in pictures. The system learns the dog’s behavior based on images. Thus, computers entered the area of mental activity, which until now had been an area of human activity.
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With this type of algorithm, machines can take on new tasks that were done by humans in the past. For example, in the interpretation of medical images and the diagnosis of cancer, where images of dogs are simply replaced by x-rays. The training course includes information about whether or not cancer has been diagnosed. After learning how to read and interpret X-rays, the system can reduce the time a doctor spends looking at images. Machines are climbing the ladder and taking over the mental work.
For practical experiences, case studies are included after each module. For some courses you need development skills in Python or ‘R’. If you are not familiar with programming languages, the documentation in the case studies is supported by code snippets. For example, code is provided to read from an external file or to view your data. You develop your skills in real world. For example, you will build your own recommendation system for movies, similar to Netflix’s recommendation system. In another study, you use traditional genetic theories to identify new candidate genes that may cause autism.
The class is not advanced, although you learn important concepts in math. From end to end, you tackle the problem directly to develop your own solution on real data.
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On the other hand, the course is very challenging because of the deep dive into mathematics and programming and the limited time of only six weeks. It’s exciting because it takes you deep into the world of data and intelligent systems, which is one of the main drivers in my business area.
However, on the other hand, the downside is that you only have a few months of access to the curriculum, and especially the videos, which are not enough. Also, you can’t download videos, only text files, which is unnecessary. The course will resume in February 2017. For consultants focusing on digital transformation, it is a must. Enjoy!
About the author: Florian Hoeppner works as a technical specialist for modern IT in North American financial services. His focus is on Enterprise Agile, DevOps, SRE combined with planning and design. Now, Florian is living the dream in New York. In recent years, AI has become a pillar of every technology and business, resulting in huge demand for AI companies worldwide. If you are looking for a way to join the movement and be a part of the success and development of AI, then an AI course is for you.
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There is no shortage of online and in-person certification courses to prove your skills in AI, but they are not all created equal. Some are vague in their approach, while others are very specific. To help guide you on your journey, we’ve rounded up 13 AI certification programs to help you advance your career.
An AI certificate certifies a set of skills you claim to have. AI certificates are digital certificates that show you the skills to design, program and maintain AI models.
General AI exam tests your skills in various programming languages, such as Java and Python programming. It also covers your knowledge of linear algebra and basic calculus. Depending on the subspecialty of the degree, a certificate program can test you in various signal processing techniques and neural network architectures.
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