Deep Learning

This course is designed to provide you with a comprehensive understanding of the fundamentals of deep learning. Deep learning is a subfield of machine learning that uses neural networks to model complex patterns in data.

This course covers the foundational concepts of deep learning, including neural networks, backpropagation, convolutional neural networks, and recurrent neural networks.

What Will You Learn?

You will learn the basics of deep learning, including the architecture of neural networks, activation functions, loss functions, and optimization algorithms. You will also learn how to build deep learning models using popular libraries such as TensorFlow.

In addition, you will learn about convolutional neural networks and recurrent neural networks, which are used for image recognition and natural language processing, respectively.

Skills You Will Gain:

• After completing this course, you will have gained the following skills:
• Understanding of deep learning concepts and their applications
• Ability to build and train deep learning models using TensorFlow
• Understanding of convolutional neural networks and their applications in image recognition
• Understanding of recurrent neural networks and their applications in natural language processing
• Ability to apply deep learning models to solve real-world problems
• Overall, this course will provide you with a strong foundation in the fundamentals of deep learning, giving you the necessary skills to build and deploy deep learning models for various applications.

Why Should I Enroll For This Course?

• Undertaking a training course in basic Deep Learning can provide numerous benefits, including:
• Understanding of the fundamentals: A basic Deep Learning course can help you understand the fundamental concepts of neural networks, activation functions, optimization algorithms, and loss functions. This understanding can serve as a strong foundation for advanced Deep Learning concepts and techniques.
• Improved problem-solving skills: Deep Learning involves developing algorithms that can automatically learn from data and improve performance over time. This process can improve your problem-solving skills as you learn how to tackle complex problems by breaking them down into simpler parts.
• Increased career opportunities: Deep Learning is a rapidly growing field with numerous career opportunities. Undertaking a basic Deep Learning course can help you acquire the skills and knowledge necessary to pursue a career in this field, including roles such as Machine Learning Engineer, Data Scientist, and AI Researcher.
• Enhanced data analysis skills: Deep Learning involves working with large datasets and analyzing complex patterns in data. A basic Deep Learning course can help you develop the skills necessary to analyze data more effectively, including data preprocessing, data cleaning, and data visualization.
• Hands-on experience: Many basic Deep Learning courses involve hands-on projects and exercises that allow you to practice building and deploying Deep Learning models. This hands-on experience can help you develop practical skills and gain real-world experience in Deep Learning.
• Overall, undertaking a training course in basic Deep Learning can provide you with numerous benefits, including a strong foundation in Deep Learning concepts, improved problem-solving skills, increased career opportunities, enhanced data analysis skills, and hands-on experience in building and deploying Deep Learning models.

Career Pathways, Average Salary and Hiring Companies: 

• After undertaking a course in the fundamentals of Deep Learning, there are several career pathways you can pursue, including:
• Deep Learning Engineer: A Deep Learning Engineer designs, develops, and implements deep learning algorithms and models that can learn from data and make predictions.The average salary for a Deep Learning Engineer in India is around ?9,00,000 per annum. Major hiring companies include Amazon, Google, Microsoft, Nvidia, and Qualcomm.
• Data Scientist – Deep Learning: A Data Scientist with a focus on Deep Learning is responsible for applying deep learning techniques to analyze and interpret large and complex data sets to extract insights and make informed decisions.The average salary for a Data Scientist with a focus on Deep Learning in India is around ?9,00,000 per annum. Major hiring companies include Accenture, Deloitte, Fractal Analytics, Genpact, IBM, Infosys, KPMG, TCS, and Wipro.
• Research Scientist – Deep Learning: A Research Scientist with a focus on Deep Learning is responsible for conducting research and developing new techniques and models for deep learning.The average salary for a Research Scientist with a focus on Deep Learning in India is around ?12,00,000 per annum. Major hiring companies include Amazon, Google, Microsoft, Nvidia, and Qualcomm.
• Machine Learning Engineer – Deep Learning: A Machine Learning Engineer with a focus on Deep Learning is responsible for developing and deploying machine learning algorithms and models that use deep learning techniques to make predictions.The average salary for a Machine Learning Engineer with a focus on Deep Learning in India is around ?9,00,000 per annum. Major hiring companies include Amazon, Google, IBM, Microsoft, Nvidia, and Qualcomm.
• Computer Vision Engineer: A Computer Vision Engineer is responsible for developing and implementing computer vision algorithms and models that can analyze and interpret visual data such as images and videos.The average salary for a Computer Vision Engineer in India is around ?8,00,000 per annum. Major hiring companies include Amazon, Google, Microsoft, Nvidia, and Qualcomm.