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Artificial Intelligence Course in Hyderabad

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Artificial Intelligence Course in Hyderabad

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About the Artificial Intelligence Course in Hyderabad

This introduction of AI ideas and workflows, machine learning, deep learning, and performance measurements is provided in this Introduction to AI. You’ll discover the differences between supervised, unsupervised, and reinforcement learning, as well as use examples and how clustering and classification algorithms can aid in the identification of AI business applications.

Artificial Intelligence Course in Hyderabad
Artificial Intelligence Course in Hyderabad

What You Will Learn in this Artificial Intelligence Course ?

Certification for Artificial Intelligence Course in Hyderabad

Do you want to learn more about Artificial Intelligence? Then Niralee’s AI course prepared by industry experts is what you need. We have experienced faculty members with expertise in cutting-edge AI applications.

Artificial Intelligence is a new trend and has huge opportunities. So, strengthen the required skills to get the best jobs in the AI sector with Niralee’s methodical AI course that offers hands-on practical experience. Immerse yourself into real-world Artificial Intelligence learning. Through the course, students can easily grasp the basic and advanced concepts of Artificial Intelligence.

Why Join The Artificial Intelligence Program?

Software Development Course in Hyderabad

Highly demanding course

In the last year, the number of AI jobs has increased by 30%. The average compensation for AI developers is INR 9 LPA.

Content

100% Guaranteed Assistance

Land a job of your dreams after completing our AI course. You will be assisted by our placement team at every step of your job search.

Software Development Course in Hyderabad

Get Job ready

A one-on-one career mentoring session that is tailored to your specific needs.

Enhancing your profile, conducting practice interviews, and receiving regular feedback are all that we provide. 

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0% interest rate

Get simple financing options with no hidden fees and a 0% interest rate.

Emerging roles in Artificial Intelligence field
  • AI Engineer
  • AI Specialist
  • Machine learning engineer
  • Data scientist
  • Research scientist
  • Business intelligence developer
  • Computer vision engineer
Who should join the Artificial Intelligence Program?
  • Graduates
  • Post Graduates
  • IT Professionals
  • Data Analysts, Business Analysts
  • Python Professionals
  • Also, anyone having interest to learn Artificial Intelligence
Get Your Dream Job

Our Artificial Intelligence curriculum is structured in such a way that it prepares you to work in the sector in just six months. Our career assistance team is accessible 24/7 to help you land your dream job.

Our placement stats

Maximum salary hike: 260%

Average salary hike: 90%

Placement success rate: 92%

Artificial Intelligence program with internship opportunity (6 months)

Highly Recommended for 2018/19/20/21/22 Passed-outs

  • The future of AI is bright because now there is more market and consumer awareness.
  • 6 months program where the classes would be led by an Live Instructor (Lifetime Recorded classes available for further reference)
  • Live Projects & Capstone projects
  • Receive Industry Recognized MNC certification After Successful course completion.
  • 100% Job Guaranteed with the help of our placement cell.
  • New Batch Starts on 01-01-2023

Why Join with Niralee Technologies?

 

Features

Other institutes

Niralee.com

1 on 1 mentorship

Internship opportunity

100% Job guarantee

Advanced hands-on course

Dedicated support team

Doubt sessions

Hackathons

Portfolio building

Affordable fees

Confused about Artificial Intelligence Course, Career, Jobs Growth? Talk to Our Certified Career Experts Guidance Today!

Accelerate your career growth with Artificial Intelligence program

  • Personalised training 
  • Industry experienced trainers and mentors
  • Industry appropriate curriculum 
  • Daily and weekly assignments 
  • Dedicated portal 
  • Mock interviews
  • One to one mentorship
  • 24/7 Support
  • Real-time projects 
  • Internship opportunity 
Artificial Intelligence Course in Hyderabad
Artificial Intelligence Course in Hyderabad

Artificial Intelligence program: A must do course

According to an Accenture study, AI could double yearly economic growth rates in 12 industrialized economies by 2035 by changing the nature of employment and establishing a new interaction between man and machine. The influence of AI technology on business is expected to boost labor productivity by up to 40% and allow individuals to use their time more efficiently.

Why is the demand for Artificial Intelligence programs high?

Mechanics and operations powered by AI have already made it easier to handle varied places with less hazards, and the trend of turning to AI is only going to grow in the future years. This is why getting an education in this profession will help you improve your talents in this area.

ore features of Artificial Intelligence program :

Learn fundamental AI topics as well as intuition training to get up to speed on everything AI Covering:

  • How to get started constructing AI with Python if you’ve never coded before.
  • How to use AI and OpenAI Gym to learn more efficiently
  • How to optimise your AI so that it can perform at its best in the real world

Artificial Intelligence program overview

Key Highlights of our program

  • Affordable rates with ample discounts
  • Dedicated learning Portal
  • Responsive website
  • Internship opportunities for Freshers
  • Real world Assignments
  • Weekly Assignments
  • Doubt Sessions
  • Timely Doubt Sessions
  • Dedicated support Team
  • Curriculums
  • Advanced Curriculums
  • 1-1 Mentorship
  • Certificates
  • Resume building Tips
  • Interview Guidance and Support

Artificial Intelligence Course curriculum

TOPICS

1 - Introduction
  • Definitions 
  • Goals of AI
  • AI Approaches
  • AI Techniques
  • Branches of AI
  • Applications of AI
2 - Problem-solving, search engines
  • General problem
  • search and control strategies
  • Exhaustive searches 
  • Heuristic search 
  • Constraint satisfaction problems
3 - Knowledge representation
  • KR Introduction
  • KR Using Predicate logic 
  • KR Using Rules
4 - Reasoning system
  • Reasoning
  • Symbolic reasoning
  • Statistical Reasoning
5 - Game Theory
  • Overview
  • Mini-Max Search Procedure 
  • Game playing with mini-max example 
  • Alpha-Beta
6 - Learning System
  • What is learning
  • Rote learning
  • Learning from examples
  • Explanation based learning
  • Discovery Theory Drove 
  • Clustering
  • Analogy 
  • Reinforcement
7 - Expert Systems
  • Introduction
  • Knowledge acquisition 
  • Knowledge base
  • working memory
  • Inference engine 
  • Expert system
  • Explanation
  • Application of expert systems
8 - Neural Networks
  • Introduction
  • Model of artificial neuron
  • Neural network architectures
  • Learning methods in neural networks 
  • Single-layer NN system 
  • Applications of neural networks
9 - Fundamentals of genetic algorithms
  • Introduction
  • Encoding
  • Operators of genetic algorithm
  • Basic genetic algorithm
10 - Natural Language Processing
  • Introduction Natural language
  • Syntactic Processing
  • Semantic and Pragmatic
11 - Foundations for AI
  • AI: Application areas
  • AI Basics (Divide and Conquer, Greedy, Branch and Bound, Gradient Descent)
  • NN basics (Perceptron and MLP, FFN, Backpropagation)
12 - Convolution Neural Networks
  • Image classification
  • Text classification
  • Image classification and hyper-parameter tuning
  • Emerging NN architectures
13 - Recurrent Neural Networks
  • Building recurrent NN
  • Long Short-Term Memory
  • Time Series Forecasting
14 - Deep Learning
  • Auto-encoders and unsupervised learning
  • Stacked auto-encoders and semi-supervised learning
  • Regularisation - Dropout and Batch normalisation
15 - Common Sense
  • Introduction Common sense knowledge and reasoning, How to teach
  • commonsense to a computer.
  • Formalisation of Common Sense Reasoning Initial attempts in the late
  • 60s and early, Renewed attempts in the late ’70s and 80s to recent time.
  • Physical World Modelling the qualitative world, Reasoning with
  • qualitative information.
  • Common Sense Ontologies Time, Space, Material.
  • Memory Organisation Short term memory (STM), Long term memory
  • (LTM).

Machine learning

1 -Foundations for ML
  • ML Techniques overview
  • Validation Techniques (Cross-Validations)
  • Feature Reduction/Dimensionality reduction
  • Principal components analysis (Eigenvalues, Eigenvectors, Orthogonality)
2 - Clustering
  • Distance measures
  • Different clustering methods (Distance, Density, Hierarchical)
  • Iterative distance-based clustering;
  • Dealing with continuous, categorical values in K-Means
  • Constructing a hierarchical cluster
  • K-Medoids, k-Mode and density-based clustering
  • Measures of quality of clustering
3 - Classification Naïve Bayes Classifier
  • Model Assumptions, Probability estimation
  • Required data processing
  • M-estimates, Feature selection: Mutual information
  • Classifier
4 - K-Nearest Neighbor's
  • Computational geometry; Voronoi Diagrams; Delaunay Triangulations
  • K-Nearest Neighbour algorithm; Wilson editing and triangulations
  • Aspects to consider while designing K-Nearest Neighbour
5 - Support Vector Machines
  • Linear learning machines and Kernel space, Making Kernels and working in feature space
  • SVM for classification and regression problems.
6 - Decision Trees
  • ID4, C4.5, CART

 

7 - Ensembles methods
  • Bagging & boosting and its impact on bias and variance
  • C5.0 boosting Ÿ Random forest
  • Gradient Boosting Machines and XGBoost
8 - Association Rule mining
  • The applications of Association Rule Mining: Market Basket, Recommendation Engines, etc.
  • A mathematical model for association analysis; Large item sets; Association Rules
  • Apriori: Constructs large item sets with mini sup by iterations; Interestingness of discovered

association rules;

  • Application examples; Association analysis vs. classification
  • FP-trees

FAQs about Artificial Intelligence Course in Hyderabad

The IT revolution is centred on artificial intelligence and has transformed the way industries operate today. The future prospects for a career in artificial intelligence are really bright since there is a huge demand for AI professionals.

For admittance into the field of artificial intelligence engineering, a bachelor’s degree in a relevant discipline, such as information technology, computer engineering, statistics, or data science, is the absolute minimum requirement.

Yes, some of the concepts can be a little difficult in the beginning. However, with the guidance of a reputed training institute having in its team experts in AI with industry experience, you can easily master the concepts.

 You can learn artificial intelligence by enrolling in a data science boot camp or joining an established training institute like Niralee.

Around INR 8 lakhs is the average yearly income for entry-level AI engineers in India, which is much more than the average wage for any other engineering graduate. The salaries for AI engineers can reach INR 50 lakhs at higher levels.

No, it is not required. Understanding AI from scratch can be challenging at first, but as you continue to devote more time to learning various AI-related concepts, it becomes more exciting and cool.

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