Understand Machine Learning Fundamentals: Gain a solid understanding of the core concepts, principles, and techniques of machine learning, including supervised learning, unsupervised learning, and reinforcement learning.
Learn AWS Machine Learning Services: Explore various AWS machine learning services such as Amazon SageMaker, Amazon Rekognition, and Amazon Comprehend. Understand their features, capabilities, and how to leverage them to build and deploy machine learning models.
Develop Practical Skills: Acquire hands-on experience in applying machine learning algorithms and techniques using AWS services. Learn how to preprocess data, train models, evaluate performance, and make predictions or classifications using AWS tools and resources.
Build and Deploy Machine Learning Models: Learn how to develop and deploy machine learning models on the AWS platform. Understand the process of data preparation, feature engineering, model training, and model deployment to create robust and scalable solutions.
Explore Advanced Machine Learning Concepts: Dive into advanced machine learning topics such as natural language processing (NLP), computer vision, and deep learning. Gain insights into advanced algorithms and techniques to solve complex machine learning problems.
Gain a comprehensive understanding of machine learning concepts and techniques, with hands-on experience using AWS services. Prepare for the AWS Certified Machine Learning Specialty exam and explore advanced topics like deep learning and natural language processing. Acquire industry-relevant skills, stay updated with the latest advancements, and expand your professional network through valuable networking opportunities.
The course covers essential machine learning topics, including data preprocessing, model training, evaluation, and deployment. Participants will gain practical experience using AWS machine learning services such as Amazon SageMaker, comprehend advanced concepts like deep learning and natural language processing, and explore real-world applications of machine learning. Additionally, they will learn about model optimization, monitoring, and best practices for ensuring the accuracy and efficiency of machine learning models.
Diana’s AWS Training Program covers a comprehensive range of AWS courses, including AWS Cloud Fundamentals, core AWS services, security and compliance, architectural best practices, cost optimization strategies, and managing and operating AWS environments. Gain practical skills in AWS implementation, resource provisioning, monitoring, troubleshooting, and automation to prepare for diverse career opportunities in the AWS ecosystem.
Upon completion of the course,
students will receive the AWS Certified Machine Learning Certification, which is recognized by employers worldwide.
The course focuses on practical
skills and real-world scenarios, providing students with the
knowledge and experience they
need to excel in a career in IT support
The course offers a high-quality
education at an affordable price,
making it accessible to individuals
who may not have the resources
to pursue more expensive
certification programs.
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Date
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Schedule
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Time
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Enroll Now
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July 11 2023
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Sat. and Sun (6 weeks)
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8 PM to 10:30 PM IST
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July 17 2023
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Sat. and Sun (6 weeks)
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8 PM to 10:30 PM IST
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July 24 2023
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Sat. and Sun (6 weeks)
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8 PM to 10:30 PM IST
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Date
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Schedule
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Time
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Enroll Now
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|---|---|---|---|
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July 11 2023
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Sat. and Sun (6 weeks)
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8 PM to 10:30 PM IST
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July 17 2023
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Sat. and Sun (6 weeks)
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8 PM to 10:30 PM IST
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July 24 2023
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Sat. and Sun (6 weeks)
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8 PM to 10:30 PM IST
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An online course degree is similar to taking a degree program on campus. Attending a live instructional course will be similar to attending a lecture but in the comfort of your location. Our Academy and your course instructor will determine the format for each course and will select the best-suited curriculum and projects for your course or program.
You will need a computer, a high-speed Internet connection, a newer version of a web browser, and access to common tools and software like word processors, email, etc. Some courses may have other software or technology requirements as well. If there are special labs included all you need is to follow your trainer’s instruction to log in to our virtual labs.
We are yet to introduce courses with Self-paced learning means you can learn in your own time and schedule. There is no need to complete the assignments and take the courses at the same time as other learners. The reason why we are choosing live instructional training over self-paced is the alignment of our students to complete and get their certifications on time for their placements or project placements at their respective organizations.
The courses are detailed in the course offerings under “Our Courses” For further information, please contact DIANA ACADEMY for Online Learning.
Online learning is not only more effective for students, but it is also better for the environment. Online courses consume 90% less energy and release 85% less CO2 per student than traditional in-person courses, according to the Open University in the United Kingdom. Online learning and multimedia material become more effective instructional tools as a result of this. Individuals and businesses can profit from helping the environment and sticking to their own environmental goals by encouraging and engaging with this form of learning.
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Date
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Schedule
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Time
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Enroll Now
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July 11 2023
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Sat. and Sun (6 weeks)
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8 PM to 10:30 PM IST
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July 17 2023
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Sat. and Sun (6 weeks)
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8 PM to 10:30 PM IST
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July 24 2023
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Sat. and Sun (6 weeks)
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8 PM to 10:30 PM IST
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|
Date
|
Schedule
|
Time
|
Enroll Now
|
|---|---|---|---|
|
July 11 2023
|
Sat. and Sun (6 weeks)
|
8 PM to 10:30 PM IST
|
|
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July 17 2023
|
Sat. and Sun (6 weeks)
|
8 PM to 10:30 PM IST
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|
|
July 24 2023
|
Sat. and Sun (6 weeks)
|
8 PM to 10:30 PM IST
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