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Course Overview

Artificial Intelligence, or AI, is a machine’s ability to think and function accordingly. Recently Artificial Intelligence has taken over the world, and each day we witness a new product from this miraculous technology. We are all utilising AI in Siri, Alexa, Linkedin, Google AI Assistant and many more such intelligent machines. Presently every business organisation requires AI to flourish in this digital world. Pursuing an Artificial Intelligence course from Digi Archarya shall make you understand the core concepts of the AI algorithm. It shall empower you to understand the technology and develop the future. Companies worldwide seek professionals adept in Artificial Intelligence and rely on them to better their business. Our distinguished approach towards training aids students in learning better and prepares them for being enviably successful in the future.

Why this course from digiacharya

Artificial Intelligence (AI) course opens doors to immense opportunities. With Digi Acharya, you grab the best instructor-led training to ace all the techniques and tools that make you stand apart. Our courses are designed to make you win and attain constant success.

TRAINED EDUCATOR

Learn from teachers with years of experience in ethical hacking

ELABORATE SYLLABUS

We insist on teaching more than what is in the books

ONLINE TEACHING

Online classes are available to learn at your will

AUTHORISED CERTIFICATION

We provide certificates credible at all organisations worldwide

Trained Educator

Learn from teachers with years of experience in ethical hacking

Elaborate Syllabus

We insist on teaching more than what is in the books

Online Teaching

Online classes are available to learn at your will

Authorised Certification

We provide certificates credible at all organisations worldwide

Our program is suitable for

Any student who has a never-ending passion for learning Artificial Intelligence can opt for the course. All you require is a 10+2 form of education in Science from a renowned university. Having Maths and Physics as compulsory subjects shall help you understand the tech concepts better than others. Apart from this, an untiring zeal to learn and imbibe technology is your fundamental prerequisite for an Artificial Intelligence course. With such qualities, you are welcome to attain the highly rewarding course of Artificial Intelligence with the best mentors of Digi Acharya.

Create a change with your Artificial Intelligence skills

Provide the much-needed push to your career with the course

Learn the subjects in-depth from the top industry experts

Course Module

Introduction to Artificial Intelligence

Digi Acharya begins with introducing Artificial Intelligence, where the students are provided with basic knowledge regarding AI, its need, application and branches. The course proceeds to define intelligence with the Turing test and making machines think alike a human brain. In the tenure, students also learn about general problem solving and how they can utilise GPS for the same. Further installing Python on Ubuntu, Mac OS X, Windows, and other operating systems. Module 1 of Artificial Intelligence is a window to what one shall learn and to which depth.

Classification and Regression Using Supervised Learning

Classification and Regression algorithms are useful in prediction during machine learning. However, both have immense differences. Module 3 of the Artificial Intelligence course at Digi Acharya focuses on helping the students disintegrate amongst the two. They learn from the basics of supervised and unsupervised learning and progress to imbibing preprocessing data, binarisation, mean removal, scaling, normalisation, label encoding and many such subjects. Module 3 also takes students to the depth of regression, single variable, multivariable, and more.

Detecting Patterns with Unsupervised Learning ∙

Module 5 of the Artificial Intelligence course of Digi Acharya deals with detecting patterns with unsupervised learning. In this process, candidates know more about unsupervised learning, i.e., the idea of building machine learning processes without utilising labelled data. Students also learn how to cluster data with K-means Algorithm, use mean shifts to estimate the number of clusters and map the clustering quality with silhouette scores. Students begin to conceptualise the Gaussian Mixture Models and build a classifier based on the same. They also begin using Affinity Propagation.

Logic Programming

Logic programming is based on logic. This indicates that a logic programming language has phrases that logically convey facts and rules. It computes by making logical inferences based on all available facts. Module 7 of Artificial Intelligence courses reveals the concepts of logical programming to the students. It also helps understand the building blocks and solve problems using logic programming. This section focuses on educating students to install Python packages. Analysing geography and learning to be a problem solver is the key motive of this module.

Genetic Algorithms

The genetic algorithm focuses on solving optimization queries. With module 9 of the Artificial Intelligence course with Digi Acharya, students shall learn the details of evolutionary and genetic algorithms. They shall also imbibe the fundamental concepts in genetic algorithms. Learning to generate a bit pattern with predefined parameters is also in the curriculum. Adding the detailed syllabus is the comprehensive guide to visualizing the evolution and solving the symbol regression problem. Towards the end of this module, students learn about building an intelligent robot controller.

Natural Language Processing

Natural language processing is a section of Artificial Intelligence that enables machines to understand human language. Students begin with learning the installation of packages. They also know tokenizing text data and the art of converting words to their base forms using stemming. Later in module 11 of the Artificial Intelligence course, students learn how to convert words to their base forms using lemmatization and learn to divide the text data into chunks. They also extract the frequency of terms using a bag of words model, build a category predictor and learn much more.

Building a Speech Recognizer

Speech recognition technology is now a household thing, and it defines comfort in a new way. With module 13 of the Artificial Intelligence course, students shall learn the core concepts of this technology. They learn to work with speech signals and visualise audio signals. Later they imbibe the skill of transforming audio signals to the frequency domain. Students can enjoy this craft and carve an artsy career out of it by generating audio signals and synthesising tones to generate music. Recognising spoken words through the extraction of speech features is another section of this module.

Artificial Neural Networks

The Artificial Neural Network or ANN is the technology that imitates the human brain’s functioning of sending signals through neurons and axons. Students shall learn about this breathtaking technology in module 15 of the Artificial Intelligence course. Not just learning, but they shall also be trained to build a neural network. The module proceeds to build a perceptron based classifier. Constructing a single and multi-layer neural network is also in the curriculum, along with building a vector quantizer, visualizing characters in an Optical Character Recognition database.

Deep Learning with Convolutional Neural Networks

The convolution neural network is a key algorithm wherein it can taken an image, assign learnable weights and enable the device to differentiate an image from another. Module 17 of Artificial Intelligence focuses on teaching students regarding the comprehensive syllabus of Convolution Neural Network or CNN. The section comprises of architecture and types of CNN. It later focuses on building a perceptron-based linear regressor. Then the syllabus proceeds on creating an image classifier using a single layer neural network and Convolutional Neural Network CNN.

AI with Python – Machine Learning & Data Preparation

Machine Learning is a crucial application of Artificial Intelligence where the computer system is programmed to learn with the data and improve with experience. The main aim of Machine Learning is to learn automatically without having to solve queries with human intervention at each step. Students shall grasp the basics of various machine learning types in Module 2 of Artificial Intelligence. They will also have an idea of common algorithms helpful in solving numerous puzzles in the future. The section also integrates data preprocessing, its techniques and labelling.

Predictive Analytics with Ensemble Learning

Ensemble learning is an application wherein multiple models are designed and generated to solve a computational problem. It’s a powerful way to increase the efficiency of any model. Module 4 of the Artificial Intelligence course from the Digi Acharya focuses on providing detailed learning regarding ensemble models. It also teaches about decision trees and building the decision tree classifier. The module progresses with Random forests and an extremely random forest classifier. Students also learn about finding optimal training parameters with the grid search.
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Building Recommender Systems

Automated recommendations are everywhere. At some point, we have all fallen into the trap. Module 6 of the Artificial Intelligence course explore the building recommender system and provides students with a deep insight into the subject. The interactive section begins with creating a training pipeline to analyse and understand the topic. It then extracts the nearest neighbours and builds a K-Nearest Neighbors classifier. Students also pursue computing similarity scores and finding similar users using collaborative filtering to build a movie recommendation system.

Heuristic Search Techniques

The heuristic is a technique that is part of Artificial Intelligence, used for solving a problem faster than traditional approaches. Module 8 of the Artificial Intelligence course is about a detailed syllabus of the heuristic search. It also enlightens students regarding the uninformed versus informed search. Students also learn and solve constraint satisfaction problems and local search techniques. Simulated annealing, constructing a string using greedy search, solving a problem with constraints are other sections of this module. One also learns to build an 8-puzzle solver.

Building Games with Artificial Intelligence

The online games market is immense, and with module 10 of the Artificial Intelligence game, we shall learn the same. The section teaches how to search algorithms in games and proceeds to combinatorial search. You also learn the minimax algorithm along with Alpha-Beta pruning. Next comes the Negamax algorithm and Installing easyAI library. Students also learn to build a bot to play Last Coin Standing and Tic-Tac-Toe. Building two bots to play Connect Four™ against each other and playing Hexapawn against each other are other exciting elements of this section.

Probabilistic Reasoning for Sequential Data

Students learn about probability reasoning in the Artificial Intelligence course, Module 12. It is the segment in AI where we use the probability concept to define the uncertainty in knowledge. Understanding sequential data and handling time-series data with Pandas are other sub-sections of Probability reasoning. Students also learn slicing and operating the time-series data. The next segment extracts statistics from time-series data and generates data using Hidden Markov Models. The module ends with identifying alphabet sequences and stock market analysis.

Object Detection and Tracking

Identifying objects in a video and interpreting them with high accuracy is known as object detection and tracking. It is a part of deep learning to set the machine automatically to recognize objects. In module 14 of the Artificial Intelligence course, one learns the install OpenCV and frame differencing. Object tracking with colourspace and background subtraction is another part of this section. Building an interactive object tracker using the CAMShift algorithm is another key element. Optical flow-based and face detection tracking form yet another pillar of this module.

Reinforcement Learning

Reinforcement learning is a form of machine learning where the computer program interacts with the environment and learn to enact it. Module 16 also tutors students regarding reinforcement training, including its key elements, types and much more. Students also learn the difference between reinforcement learning and supervised learning. These courses are accompanied by real-world examples to explain the students clearly. This module teaches students the building blocks of reinforcement learning while creating and building a learning environment.

Artificial Intelligence Platforms & Tools

Artificial Intelligence (AI) is where the machine mimics the human brain and solves queries with learning, analysing, reasoning and utilising in-built knowledge and great intelligence. AI is all about machine learning, deep learning, prebuilt algorithms and code frameworks. Google AI Assistance, Microsoft Azure, Infosys Nia, TensorFlow, RainBird are some of the strongest AI platforms .

Amazon Web Services

NuPIC

TensorFlow

AI-ONE Analyst Toolbox

Lime

Caffe

What skills you will gain

Machine Learning

The process of “teaching” a machine to exhibit intelligence is known as machine learning. Machine learning creates a model from data that allows a device to make intelligent predictions without using a coded algorithm. Machine learning uses three approaches i.e., supervised learning, unsupervised learning, and reinforcement learning. There is no way to learn AI without first mastering machine learning. It’s AI that enables a machine to “behave” intelligently. With Digi Acharya’s comprehensive AI course, students acquire Machine learning as one of the critical skills.

Deep Learning

Another key skill achieved from The Artificial Intelligence course of Digi Acharya is Deep Learning. It is a sub-section of machine learning and is a method for the AI system to “learn. It employs multiple layers to extract deeper details from an image or a sound. Deep Learning is used in various applications, including image recognition, speech recognition, and audio recognition. It has numerous applications and is a skill learned in an AI course. The Digi Acharya’s AI course enlightens the students with qualities of Deep Learning and how students can incorporate it.

Data Science

Data Science is a unique arena of science, and it combines mathematics, algorithms and statistics to read and extract meaningful information from structured or unstructured data. Data science is an essential aspect of Artificial Intelligence and other fields that rely heavily on data analysis. Data Science is a vital skill that students of AI must imbibe from their course. Luckily, the comprehensive curriculum at Digi Acharya encompasses Data Science and prepares its students with this crucial skill. TensorFlow, PyTorch, and Jupyter notebook are data processing platforms in Data Science.

Neural Networks

Neural networks or artificial neural networks (ANNs) mimic the human brain. Like neurons in the brain, ANNs have nodes connected to a network to transmit input data in the form of “signals”. ANN applications include 3D reconstruction, handwritten note recognition, spam filtering, gaming, and more. With the help of an algorithm, they recognize hidden patterns and correlate, cluster and classify them. They further utilize them to learn, gain knowledge and continuously improve. The Artificial Intelligence course at Digi Acharya provides a basic understanding of the subject.

Language

The Artificial Intelligence course at Digi Acharya enables the students to grasp languages and tools that shall be effective during their projects. One such programming language used worldwide is Python.It is widely used because of the elaborate library and ease of use. Python can be learned by people with no prior knowledge of programming.
Knowledge of programming in Python and a few other languages is required to become an AI expert. Other languages used in Artificial Intelligence include Java, PROLOG, R, LISP, and C++.

Machine Learning

Machine Learning

The process of “teaching” a machine to exhibit intelligence is known as machine learning. Machine learning creates a model from data that allows a device to make intelligent predictions without using a coded algorithm. Machine learning uses three approaches i.e., supervised learning, unsupervised learning, and reinforcement learning. There is no way to learn AI without first mastering machine learning. It’s AI that enables a machine to “behave” intelligently. With Digi Acharya’s comprehensive AI course, students acquire Machine learning as one of the critical skills.

Deep Learning

Deep Learning

Another key skill achieved from The Artificial Intelligence course of Digi Acharya is Deep Learning. It is a sub-section of machine learning and is a method for the AI system to “learn. It employs multiple layers to extract deeper details from an image or a sound. Deep Learning is used in various applications, including image recognition, speech recognition, and audio recognition. It has numerous applications and is a skill learned in an AI course. The Digi Acharya’s AI course enlightens the students with qualities of Deep Learning and how students can incorporate it.

Data Science

Data Science

Data Science is a unique arena of science, and it combines mathematics, algorithms and statistics to read and extract meaningful information from structured or unstructured data. Data science is an essential aspect of Artificial Intelligence and other fields that rely heavily on data analysis. Data Science is a vital skill that students of AI must imbibe from their course. Luckily, the comprehensive curriculum at Digi Acharya encompasses Data Science and prepares its students with this crucial skill. TensorFlow, PyTorch, and Jupyter notebook are data processing platforms in Data Science.

Neural Networks

Neural Networks

Neural networks or artificial neural networks (ANNs) mimic the human brain. Like neurons in the brain, ANNs have nodes connected to a network to transmit input data in the form of “signals”. ANN applications include 3D reconstruction, handwritten note recognition, spam filtering, gaming, and more. With the help of an algorithm, they recognize hidden patterns and correlate, cluster and classify them. They further utilize them to learn, gain knowledge and continuously improve. The Artificial Intelligence course at Digi Acharya provides a basic understanding of the subject.

Language

Language

The Artificial Intelligence course at Digi Acharya enables the students to grasp languages and tools that shall be effective during their projects. One such programming language used worldwide is Python.It is widely used because of the elaborate library and ease of use. Python can be learned by people with no prior knowledge of programming.
Knowledge of programming in Python and a few other languages is required to become an AI expert. Other languages used in Artificial Intelligence include Java, PROLOG, R, LISP, and C++.

Career Roles

Digi Acharya’s Artificial Intelligence course is designed as a comprehensive study material. It caters to the student’s knowledge base with both theoretical and practical knowledge making them adept to ace every opportunity.

Ace the role of AI engineer with renowned companies worldwide

Acquire the post of Research Scientist at government universities

Be a Machine Learning Engineer in the top IT Firm

Serve the globe by being a Robotics Engineer to design OS

Course Experts

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FAQ's

As the world develops, Artificial Intelligence shall be in demand, and students may not have a shortage of opportunities.

Companies such as Google, Facebook, Microsoft, Wipro, IBM and many others are eager to recruit AI students.

Digi Acharya focuses on the overall development of its students. Students obtain a perfect balance of theoretical and practical knowledge in their tenure.

Our teachers are willing to guide the students even after the course completion if needed.

Artificial Intelligence is not a challenging course if one has a passion for learning and developing technology.