Advanced AI and Neural Networks: Techniques and Applications

Self-Paced Learning
2.5 Hours
Beginner

This Course Covers: Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Generative Adversarial Networks.

$ 9.99
Self-Paced

About this Course:

AI is revolutionizing the way we live, work and communicate. At the heart of AI is Deep Learning. Once a domain of researchers and PhDs only, Deep Learning has now gone mainstream thanks to its practical applications and availability in terms of consumable technology and affordable hardware.

The demand for Data Scientists and Deep Learning professionals is booming, far exceeding the supply of personnel skilled in this field. The industry is clearly embracing AI, embedding it within its fabric. The demand for Deep Learning skills by employers -- and the job salaries of Deep Learning practitioners -- are only bound to increase over time, as AI becomes more pervasive in society. Deep Learning is a future-proof career.

Within this series of courses, you’ll be introduced to concepts and applications in Deep Learning, including various kinds of Neural Networks for supervised and unsupervised learning. You’ll then delve deeper and apply Deep Learning by building models and algorithms using libraries like Keras, PyTorch, and Tensorflow. You’ll also master Deep Learning at scale by leveraging GPU accelerated hardware for image and video processing, as well as object recognition in Computer Vision.

Throughout this program you will practice your Deep Learning skills through a series of hands-on labs, assignments, and projects inspired by real world problems and data sets from the industry. You’ll also complete the program by preparing a Deep Learning capstone project that will showcase your applied skills to prospective employers.

This program is intended to prepare learners and equip them with skills required to become successful AI practitioners and start a career in applied Deep Learning.

Course Objectives:

  • Fundamental concepts of Deep Learning, including various Neural Networks for supervised and unsupervised learning.
  • Build, train, and deploy different types of Deep Architectures, including Convolutional Networks, Recurrent Networks, and Autoencoders.
  • Application of Deep Learning to real-world scenarios such as object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers.
  • Master Deep Learning at scale with accelerated hardware and GPUs.
  • Use of popular Deep Learning libraries such as Keras, PyTorch, and Tensorflow applied to industry problems.

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Sudhanshu Pandey

Software Engineer

Sudhanshu is Redhat Certified and a Computer Science graduate. He has worked on multiple technologies including Devops, ML, Python, Redhat Linux, MySQL, MongoDB, Cloud Computing, web development and mobile app development. He is currently working as an ML engineer for a startup and as a trainer on a content delivery team for Linuxworld.

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Khalil Demeri​

Cloud Solutions Architect

Khaleel has many years of experience in servers administration on Linux and Windows platforms, managing 4000+ servers running different flavors of Linux and web hosting control panels. He helps the team to deal with Windows (MCSE) and Linux Server related issues and services administration. Install, configure and integrate system/solution/OS at site and remotely.

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Saurabh Khan​

Cloud Coach

Saurabh is an enthusiastic instructor and accomplished Cloud Engineer. With a solid background in architecting cloud solutions and hands-on experience in configuring and deploying applications on leading cloud platforms like Azure, GCP, and AWS, Saurabh possesses a wealth of knowledge to share with learners.

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John Morah

Azure Architect

John is an experienced instructor and highly skilled Cloud Architect who brings a wealth of technical expertise to the table. With a career that began in January 2001, John has been fixing computers and providing technical training and support on Microsoft and Google technologies for over two decades.

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Arjun Sasikumar

Cloud Architect

Arjun has 10+ years of IT experience. Currently working as a Google Cloud Consultant in a Multi-National Company. He is holding certifications in Google Cloud Digital Leader , Google Cloud Associate Cloud Engineer and Google Cloud Professional Cloud Architect.

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Godfrey Chatira

Azure Solutions Architect

An experienced Azure Solutions Architect, with a proven track record of designing and implementing complex cloud solutions on the Microsoft Azure platform. With expertise in cloud architecture, infrastructure, security, and governance, I help organizations to maximize their investments in cloud by providing tailored solutions that align with business goals and technical requirements.

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Don Restarone

Software Engineer

End to end software architect with a proven track record for building high achieving MVP's, enterprise applications and unlocking millions of dollars in revenue for startups and founders.

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Fady Ibrahim

Google Cloud Champion Innovator

Google Cloud Champion Innovator specializing in Modern Architecture. Fady is also a Google Cloud Insider and Google Cloud Authorized Trainer.

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Gouthami Matavalam​

Senior Technical Architect

A dynamic and positive Software Engineering coach with a knack for strategic problem-solving and troubleshooting. With extensive experience in Java and Java Frameworks, Gouthami brings a structured and creative approach to coaching, helping clients achieve their personal and professional goals through tailored guidance and support. Her enthusiasm and expertise make learning engaging and effective.

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Rahees Khan

Cloud Engineer

With a Bachelor of Technology degree in Computer Science from Lovely Professional University, I have a strong foundation in modern application architectures and microservices-based deployments. I have demonstrated proficiency in Docker, Kubernetes, and OpenShift, as well as Infrastructure as Code tools such as Ansible and Terraform. I have leveraged my skills to optimize applications across Kubernetes environments, minimize vulnerabilities in microservices, and automate the provisioning of infrastructure on Google Cloud.

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Jeff Fudge

Director of Solutions Architecture & Engineering

Things I am passionate about: Technology, Community, Cyber Security, AWS and all things Cloud. I have strengths in cloud migration and strategy, PCI compliance, infrastructure consolidation and the design and implementation of high performance architectures. I enjoy working with business leadership and external partners on digital strategy and solution roadmaps. What I've been: Cloud Practice Director, CIO, CTO, VP of Technology, Director of Infrastructure. What I am now: Director of Solutions Architecture & Engineering at JetSweep and AWS User Group Leader. Who I am: A passionate, high energy, sarcastic, "glass is probably fuller than it looks" kind of guy.

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