Anyone who is a fan of online learning has probably heard of Udacity before. This e-learning platform is the leading one for data science, business, computer science, and technology-based courses.
Because of this, it is an excellent platform to choose if you’re interested to be an advanced computer vision expert or a machine learning course.
If you’re interested in finding the best computer vision courses offered by Udacity, then you will find this post helpful. Here, we have rounded up the top 9 best Udacity courses to try if you’re interested in this topic.
Keep reading to find the best Udacity computer vision courses for you!
1. Intro to Machine Learning
You will begin your education in this Nano-Degree program by learning the core machine learning techniques, starting with data cleaning and supervised models.
After that, this course will focus on both supervised and unsupervised learning.
The most beneficial aspect of this curriculum is that at each stage, you will be able to put your newly acquired previous knowledge into practice by working on coding exercises and computer vision projects.
This Nanodegree program consists of three courses that will teach you about various supervised machine learning concepts.
Some examples of these algorithms are regression, decision trees, perceptron algorithms, support vector machines, naive Bayes, evaluation metrics, and others.
On top of that, you will be instructed in deep learning and shown how to construct an image classifier.
The next step is for you to become familiar with unsupervised learning methods such as clustering, hierarchical, and density-based clustering, as well as Gaussian Mixture Models and Dimensionality Reduction.
You will have the opportunity to participate in projects that are based in the real world to help you to apply your learning, and if you ever get a bit stuck, you also have access to technical mentor support.
You will also get access to helpful services that will provide support for upgrading your resume, review of your GitHub profile, and evaluate of your LinkedIn page.
This course is geared specifically toward individuals who are proficient in Python but have not yet explored the various aspects of machine learning.
It’s also useful to individuals who have the fundamental knowledge of probability and statistics.
2. AI Programming
The fundamentals of artificial intelligence will be laid out for you in this program. Through this course, you will gain knowledge of programming tools such as Python, NumPy, and PyTorch.
You’ll learn essential mathematical skills for AI, such as calculus and linear algebra, with the help of this program.
You will also become familiar with the fundamental processes of neural networks, such as backpropagation and gradient descent.
This Nano Degree Program is comprised of a total of 5 classes. These include:
- Intro to Python,
- Pandas, Jupyter Notebook, Anaconda, NumPy, and matplotlib
- Essentials of Linear Algebra
- Calculus Essentials
- Neural Networks
Individuals who already have some introduction to computer vision skills or knowledge in algebra fundamentals, as well as programming in any language, are the ideal candidates for this course.
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3. AI For Trading
This is another Nano-Degree Program that is geared toward individuals who are interested in using AI to work in the stock market.
In this course, you will become familiar with the fundamentals of quantitative analysis, such as the processing of data, the production of trading signals, and the management of portfolios.
After completing this Nano-Degree Program, you will be able to utilize Python to design a multi-factor model with optimization, develop trading strategies, and work with historical stock data.
Individuals who have intermediate Python programming knowledge and are conversant with statistics, linear algebra, and calculus are the perfect candidates for this program.
4. Become a Computer Vision Expert
By completing this program you will learn how to develop programs for analyzing photos, implementing feature extraction, and recognizing objects by making use of deep-learning models.
Through this course, you will master everything from the fundamentals to analyze images and image processing to how to construct and modify convolutional neural networks.
The computer vision tasks included in this Nano-degree program include automatic picture captioning, facial keypoint detection, and landmark detection and tracking.
In addition to this, you will study navigation and flight techniques that can be used for drones and self-driving cars.
You will have access to support from a technical mentor if you ever get a bit confused with the course material, and you will also receive help with writing your resume, and setting up a LinkedIn profile so prospective employers can contact you easily.
If you’re proficient in Python, statistics, machine learning, and deep learning at an intermediate level then this is the course for you.
5. Intro To Machine Learning
This is a free machine-learning course for beginners. You will leave this course with a comprehensive understanding of the fundamentals of machine learning.
To enroll in this free course, you don’t need any prior experience in the subject matter., and this class is open to participation from anyone who is just starting in this kind of education.
This kind of program is designed to build up some basic skills so that you can then apply to one of the more comprehensive courses that Udacity offers.
6. Intro To TensorFlow
Udacity offers another free machine learning course for students at an intermediate level. You will learn how to construct deep learning applications with the help of TensorFlow by taking this course.
You will get the opportunity to work on projects and create your state-of-the-art image classifiers as well as other deep-learning models in this course.
In addition to that, you will become familiar with more advanced deep-learning techniques and algorithms.
However, you must have a background in linear algebra and programming in Python before joining this course as though it is for beginners the content can still be quite complicated.
7. Intro To TensorFlow Lite
This course will help you to understand how to use deep learning models can be used on embedded and mobile devices using TensorFlow Lite. This course is targeted at people who have some basic skills in this area already.
Once you have finished this course, it will be simple for you to integrate your deep learning models into any of your apps.
However, prior knowledge of the TensorFlow Lite deep learning framework as well as Object-Oriented Programming, Python, Swift, Android, and machine learning was required for this class.
8. Machine Learning Engineer
This is a Nano-Degree program that is meant for individuals who already have an understanding of the fundamental ideas of machine learning.
You will receive hands-on experience with utilizing Amazon SageMaker in this program, allowing you to deploy trained models to a web application and evaluate the performance of your models.
There are a total of 4 classes required to complete this Nanodegree program.
You will learn how to construct machine learning algorithms and how to prepare them for use in scalable production systems if you enroll in these courses.
After that, you will learn how to integrate machine learning models into a web application.
Throughout this program, you will work on a variety of machine learning case studies.
Analyze the purchasing patterns of people at Starbucks, work through a real-world dataset and challenge offered by Arvato Financial Services, which is a company owned by Bertelsmann, and develop a project to determine the breeds of dogs based on pictures of them.
Included in the curriculum is an Introduction to Software Engineering course.
Those who are proficient in Python programming and have an intermediate understanding of the methods used in machine learning will find this course very interesting and useful to them in their professional careers.
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- Get the skills you need
- Learn at your own pace
"I couldn't be more excited!"
9. Deep Learning
You will have a comprehensive understanding of Deep Learning after completing this Nano-Degree program offered by Udacity.
Convolutional networks used in image recognition, recurrent neural networks for sequence generation, and generative adversarial networks for picture generation are all going to be constructed by you throughout this study.
You will also learn how to perform gradient descent and backpropagation using NumPy matrix multiplication, how to prevent overfitting of training data and how to reduce the error of a network, as well as how to construct and train neural networks for sentiment analysis, and other related topics.
You will also learn how to speed up the training of neural networks by making use of Amazon’s GPUs as part of this Nanodegree curriculum.
CNN’s Sebastian Thrun received an explanation from the instructor about how to detect skin cancer.
Those who are familiar with Python programming at an intermediate level and have previous experience working with NumPy and pandas and people who are familiar with mathematical concepts such as