AI for All

Did you know? 54% of executives say AI solutions implemented in their businesses have already increased productivity. Dive deeper into the business opportunities of AI as well as the current state of technology and innovation, it’s limitations and the solution architecture powered by AI. What is AI? How can it help in your business? How can you leverage AI for your company or organization to take a step ahead towards the future of businesses? Learn with Neuron Academy’s ‘AI For All’ Start your AI journey now!


The program is then structured around 5 core modules

AI Fundamentals

In this module, we will showcase the state-of-the-art technologies in different sectors and how AI algorithms can be leveraged for better business opportunities. We will discuss how algorithms are ported to the hardware so that cohorts can understand exactly how these ML algorithm works.

Machine Learning (ML)

This module drives straight into the ML basics and techniques to solve the most common data problems along with discussions on real case studies with practitioners from various industries. The data preparation techniques will be covered in this module.

Big Data

What is big-data and how the data storage works. We will talk about the data- storage devices like NFS and HDFS.

DL DevOps essentials

Here we will work on the advanced DevOps tools that are used in the industries for the ML model deployments along with model versioning and management. Insights into how the datacenters are managed and used for the DL modelling along with hybrid cloud architectures, DL model life cycle management including topics like ModelDB, model Governance, model versioning, data governance & API integrations.

Deep learning Pre-Requisites

Understand the DL acceleration cycle on the hardware acceleration devices. A basic understanding of real-time data labelling tool “ADVIT”, which is the proprietary tool of the Automaton AI.

Neural Networks and Deep Learning (DL)

Leveraging the machine learning knowledge acquired previously, this module will challenge professionals to get to the cutting edge of current AI technology. After a theoretical introduction to Neural network and their architecture, we will about the most advanced tools and frameworks such as Pytorch, TensorFlow, ONNX, Keras and café, applying the theoretical knowledge to some transfer learning applications. Focus on how we can leverage any DL models on the Hardware accelerator like GPU, DPU and TPU. By the end of this module, CNN, GAN, and conversational AI will be part of every cohort’s knowledge stack.

The current state of AI in society

Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making and already it is transforming every walk of life. In this module, we will discuss AI's application across a variety of sectors, address issues in its development, and offer recommendations for getting the most out of AI while still protecting important human values.

AI in Business

Most people are not very familiar with the concept of artificial intelligence (AI), or are not sure what is it & how it would affect their companies. Everyone knows that there is considerable potential for altering business processes using AI, but not clear how it could be deployed within their own organizations. We will start with a summary of what AI is at a conceptual level, without getting sidetracked by the detailed knowledge that while essential, can distract from thinking about your business. This series of modules covers the application of ML and Deep Learning into real life. We will talk about the DL end-to-end pipeline and talk about AI ethics. How can an existing company re-brand themselves as an AI operator in their product? We will also talk about how AI will transform business in a real-life scenario. The focus of this section is to showcase the implementation of several projects while learning and discovering the most appealing area in which cohorts would like to delve deep. We will talk about how to run an AI-based start-up including the team building, infrastructure needs, client acquisition, etc.

Starting an AI project

We will walk you through the typical process to start an AI project within your organization. This will include from start on analyzing the problem statement. Then we will understand how data preparation is needed to make sure that the problems which you are trying to solve. We will also talk about how to monetize your own data and follow best practices to protect your data. Then we will talk about the different techniques which you can use to solve the problems showing various angles to solve the same problem. Now that we have solved the problem, what steps do we need to need to take to reduce time and cost for deploying the solution and how can we maintain the lifecycle and manage the solution. Then we will explain to you how we can package the solution and how to monetize it.


Aatish Langhee

“Aatish is a Artificial intelligence and Deep learning professional, a application Engineer who has keen interest in delivering innovative and cutting edge AI, Machine Learning to enterprise and developing tomorrow’s advances in AI. He is Post Graduated from College of Engineering Pune (COEP) in VLSI and Embedded Systems

Mukesh Muthiyan

Mukesh has an extensive experience in the industry with more than 10 years of work experience. He holds various skills and has created multiple AI tools for various companies.

Vinay Gundecha

Vinay’s area of expertise includes Financial Analysis, Business analytics and data science. He has mastered in tools like advanced Microsoft Excel, VBA, Python, Power Bi & R

Tuition & Financing

Rs. 25k


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