- Instructor: admin
- Lectures: 19
- Students: 50
- Duration: 10 weeks
Cloud Computing Online Courses
Cloud computing is one of the most advanced and widely used in the field of IT. Cloud computing is needed for storing data, networking, analytics, servers, intelligence, and much more. Almost every company uses cloud computing programs to store their data in the cloud for easy access.
Several websites and applications make use of cloud computing services to deliver the best possible results instantly. Some of the most widely used cloud computing services are AWS, AI with machine learning, DevOps, and Apigee. Since these services are provided through the cloud, there is no need for a personal set up as all the main work will be done in the cloud.
Learning more about these cloud computing services is important as it will help you to bring the best out of these services. You can go for our cloud computing online courses to understand more about these services.
Our cloud computing online course is about 30 hours long and all the important topics are covered in the video. All you need to do is spend 30 hours of your time and at the end, you will have learned about the cloud computing services.
By learning cloud computing services, you will increase your chances of securing a job in the IT sector as these are the most sought skills in the IT industry. So you should not think much about it and start learning about cloud computing through our course. All you need to do is spend 30 hours and learn about cloud computing from basics to advanced.
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Course Content
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Lecture 1.1Introduction with Artificial Intelligence.
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Lecture 1.2ML and other related terms to AI.
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Lecture 1.3A working example of AI and ML.
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Lecture 1.4These simple tasks are to make you understand how AI
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Lecture 1.5and ML can find their applications in real life.
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Lecture 1.6Python libraries for ML.
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Lecture 1.7Setting up Anaconda development environment.
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Lecture 1.8Verifying proper installation of Anaconda environment.
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Lecture 1.9Getting into core development of ML.
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Lecture 1.10Different ML techniques.
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Lecture 1.11Introduction of Ai with Deep Learning
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Lecture 1.12PyTorch Fundamentals: Matrices
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Lecture 1.13PyTorch Fundamentals: Variables and Gradients
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Lecture 1.14Linear Regression with PyTorch
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Lecture 1.15Logistic Regression with PyTorch
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Lecture 1.16Feedforward Neural Network with PyTorch
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Lecture 1.17Convolutional Neural Network (CNN) with PyTorch
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Lecture 1.18Recurrent Neural Networks (RNN)
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Lecture 1.19Long Short-Term Memory Networks (LSTM)
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