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Eligibility:Bachelor’s Degree in Computer Science, Information Technology, Information Systems, Electrical, Electronics, Mechanical Engineering or other STEM Majors like Math & Science.

Start your journey on Cloud computing with training and internship opportunities. Begin as a Cloud Administrator to steadily advance your career, vertically to Cloud Architect, or explore opportunities to grow to other technologies.

Eligibility: Bachelor’s Degree in Computer Science, Information Technology, Information Systems, Electrical, Electronics, Mechanical Engineering or other STEM Majors like Math & Science.

As a Cloud Administrator Intern, you would learn and perform the following responsibilities:

Bachelor’s Degree in Data Science, Math, Statistics, Computer Science, Information Systems or Information Technology. Begin as a Cloud Administrator to steadily advance your career, vertically to Cloud Architect, or explore opportunities to grow to other technologies.

Eligibility: Bachelor’s Degree in Computer Science, Information Technology, Information Systems, Electrical, Electronics, Mechanical Engineering or other STEM Majors like Math & Science.

Eligibility: Bachelor’s Degree in Computer Science, Information Technology, Information Systems, Electrical, Electronics, Mechanical Engineering or other STEM Majors like Math & Science.

As a Testing Intern, you will acquire valuable skills and knowledge in the field of software testing. Your learning experience will encompass the following key areas:

Eligibility: Bachelor’s Degree in Data Science, Math, Statistics, Computer Science, Information Systems or Information Technology. Those who begin as Entry Level Data Engineers can pursue a career in Data Engineering, Data Analysis, or Data Science and eventually advance to become Technical Architects, Solution Architects, Chief Data Scientists, or to lead the entire practise.

As an AI/ML Intern, you will gain valuable insights and skills in the dynamic field of Artificial Intelligence and Machine Learning. Here's what you can expect to learn.

What you’ll learn:

• Acquire a solid understanding of the foundational concepts and principles behind Artificial Intelligence and Machine Learning.
• Learn the crucial step of cleaning and transforming raw data into a suitable format for machine learning models.
• Understand the principles of both supervised learning (classification, regression) and unsupervised learning (clustering, dimensionality reduction).
• Gain hands-on experience in developing machine learning models using popular frameworks and libraries such as TensorFlow or PyTorch.
• Model Evaluation: Learn how to assess the performance of machine learning models, including metrics like accuracy, precision, recall, and F1 score.
• Understand the importance of feature selection and engineering to enhance the performance of machine learning models.
• Dive into the world of deep neural networks, learning about architectures like convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
• Explore the applications of machine learning in understanding and processing human language.
• Gain insights into how mUnderstand the ethical implications of AI/ML, including bias in algorithms and responsible AI practices.achine learning is applied in computer vision tasks, such as image recognition and object detection.
• Learn the process of deploying machine learning models into production environments for practical applications.
• Collaboration and Communication: Develop skills in collaborating with team members, presenting findings, and effectively communicating complex concepts.