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Artificial Intelligence Training in Hyderabad

(4.9) 19000 Ratings
  • Join the Best Artificial Intelligence Course in Hyderabad to Master AI Concepts, Tools, and Real-World Applications.
  • Flexible AI Training Options: Choose from Weekday, Weekend, or Fast-Track Batches Based on Your Schedule.
  • Artificial Intelligence Training Institute in Hyderabad Offering Hands-On Learning with Industry Projects.
  • Learn Key Topics Including Machine Learning, Deep Learning, Natural Language Processing, and Computer Vision.
  • Gain Practical Experience Through Live Projects and Real-Time Assignments Led by Skilled AI Professionals.
  • Get Career Support Including Resume Building, Mock Interviews, and Placement Assistance in AI and Data Science Roles.

Course Duration

55+ Hrs

Live Project

3 Project

Certification Pass

Guaranteed

Training Format

Live Online (Expert Trainers)
WatchLive Classes
Course fee at
₹14500

₹18000

12012+

Professionals Trained

10+

Batches every month

3778+

Placed Students

325+

Corporate Served

What You'll Learn

Master machine learning skills to create smart, data-driven AI solutions.

Artificial Intelligence Course in Hyderabad Learn deep learning networks to solve complex real-world problems effectively.

Gain practical experience in NLP and computer vision using Python and TensorFlow.

Create AI models with live projects to add more hands-on knowledge.

Learn ethical AI best practices to create responsible and unbiased intelligent systems.

Artificial Intelligence Training in Hyderabad helps you get ready for high-in-demand tech jobs quickly.

A Comprehensive of Artificial Intelligence Course Overview

The Artificial Intelligence Training in Hyderabad provided by Learnovita features a comprehensive and carefully crafted curriculum aimed at developing both fundamental and advanced AI skills. This Artificial Intelligence Course in Hyderabad program covers essential aspects of AI, including the mastery of machine learning algorithms, the intricacies of neural networks, and the application of data analytics for informed decision-making. Artificial Intelligence Certification Course in Hyderabad through hands-on projects, employing state-of-the-art AI tools and methodologies. Guided by seasoned experts, students delve into best practices and the latest trends, arming themselves with the expertise required to drive innovation in AI, optimize data strategies, and thrive in the dynamic field of artificial intelligence.

Additional Info

Exploring Future Advancements in Artificial Intelligence

  • Autonomous Systems: AI-driven advancements in algorithms, sensor technologies, and robotics are propelling the development of autonomous systems capable of executing complex tasks without human intervention. This includes self-driving cars, drones, robotic assistants, and crewless aerial vehicles (UAVs) for diverse applications in transportation, logistics, healthcare, and defence.
  • Explainable AI (XAI): As AI systems become more sophisticated and pervasive, the need for transparency and accountability in AI decision-making processes grows. Explainable AI (XAI) focuses on developing algorithms and techniques that offer interpretable explanations for AI predictions and decisions, enabling users to understand, trust, and audit AI systems.
  • AI-Powered Healthcare: AI is set to transform healthcare by enabling more accurate diagnosis, personalized treatment, and predictive analytics. Future advancements in AI-powered healthcare include the development of predictive models for disease detection and prognosis, AI-assisted medical imaging and diagnostics, and virtual healthcare assistants for patient monitoring and care management.
  • Natural Language Understanding: Breakthroughs in natural language processing (NLP) and understanding are driving advancements in conversational AI, virtual assistants, and human-computer interaction. Future AI systems may achieve greater fluency, context awareness, and empathy in understanding and generating human-like language, enabling more natural and intuitive interactions with users.
  • AI for Climate Change and Sustainability: AI technologies hold great potential to address global challenges such as climate change, resource scarcity, and environmental sustainability. Future advancements may include AI-powered predictive models for climate forecasting, optimization algorithms for energy efficiency and resource management, and AI-driven solutions for renewable energy, agriculture, and conservation.
  • Ethical AI and Bias Mitigation: As AI becomes increasingly integrated into society, there is a growing awareness of ethical concerns, biases, and fairness issues in AI systems. Future advancements may focus on developing ethical AI frameworks, bias detection and mitigation techniques, and mechanisms for ensuring AI systems uphold principles of fairness, accountability, and transparency.
  • AI-Augmented Creativity: AI technologies are expanding the boundaries of human creativity by enabling new forms of artistic expression, design innovation, and content generation. Future advancements may include AI-generated music, artwork, literature, and design prototypes that inspire and collaborate with human creators in novel ways.
  • AI in Education and Lifelong Learning: AI has the potential to revolutionize education by personalizing learning experiences, adaptive tutoring, and lifelong skill development. Future advancements may include AI-driven learning platforms, intelligent tutoring systems, and personalized learning pathways that cater to individual needs, preferences, and learning styles.

Core Tools and Platforms for AI Development

  • TensorFlow: TensorFlow is an open-source framework developed by Google for designing and training machine learning models. It supports a wide range of machine learning and deep learning algorithms, allowing developers to build and deploy scalable AI applications. TensorFlow's flexible architecture enables efficient model training on both CPUs and GPUs. It also provides extensive libraries and tools for neural network design and optimization.
  • PyTorch: PyTorch is another popular open-source framework favoured for its dynamic computation graph and ease of use. It allows developers to build and train deep learning models with a straightforward interface and robust support for GPU acceleration. PyTorch’s modular design and user-friendly API facilitate rapid prototyping and experimentation. Its strong community support ensures access to a wealth of resources and pre-trained models.
  • Keras: Keras is a high-level API designed to simplify the process of building and training neural networks. It provides a user-friendly interface that allows developers to create complex models with minimal code. Keras can run on top of TensorFlow, Theano, or Microsoft Cognitive Toolkit, offering flexibility and ease of integration. Its modularity and clear documentation make it an excellent tool for both beginners and experienced practitioners.
  • Scikit-Learn: Scikit-Learn is a versatile library for machine learning in Python, providing simple and efficient tools for data mining and data analysis. It offers a wide range of algorithms for classification, regression, clustering, and dimensionality reduction. Scikit-Learn's user-friendly API and thorough documentation facilitate rapid implementation and experimentation. It integrates well with other scientific libraries like NumPy and Pandas for data manipulation and analysis.
  • Jupyter Notebook: Jupyter Notebook is an open-source web application that allows developers to create and share documents containing live code, equations, visualizations, and narrative text. It supports interactive computing and data visualization, making it a valuable tool for exploratory data analysis and model prototyping. Jupyter Notebook’s integration with various programming languages and libraries enhances its versatility in AI development. It also facilitates collaboration and reproducibility in data science projects.
  • Apache Spark: Apache Spark is a powerful open-source distributed computing system designed for processing large-scale data. It supports in-memory data processing, which accelerates machine-learning tasks and complex data analytics. Spark’s MLlib library provides a range of machine-learning algorithms and tools for model training and evaluation. Its ability to handle big data and integrate with various data sources makes it essential for large-scale AI applications.
  • H2O.ai: H2O.ai offers a suite of open-source tools and platforms for building machine learning and AI models. Its H2O framework supports scalable and distributed machine learning, making it suitable for handling large datasets. H2O.ai also provides AutoML capabilities to automate model selection and hyperparameter tuning. Its integration with popular programming languages and platforms facilitates seamless deployment and model management.

Leading Organizations Hiring AI Experts

  • Google: Google stands at the forefront of AI innovation, actively advancing research in machine learning, natural language processing, and computer vision. Its AI technologies are embedded in critical products such as Google Search, Google Assistant, and the Google Cloud AI Platform. Google continuously develops sophisticated AI models to enhance user experience and provide cutting-edge solutions. The company's AI efforts drive significant improvements in search accuracy, personalized assistance, and cloud-based AI services.
  • Amazon: Amazon extensively utilizes AI across its diverse business operations, including e-commerce, cloud services (Amazon Web Services), and intelligent technology. The company applies AI to refine product recommendations, optimize inventory management, and enhance logistics efficiency. Through its voice assistant, Amazon Alexa, and other smart devices, Amazon demonstrates its commitment to AI-driven innovations. The integration of AI helps Amazon streamline operations and deliver tailored experiences to its customers.
  • Microsoft: Microsoft is a leading force in AI development, offering a suite of AI-powered solutions through its Azure cloud services, Office 365, and cognitive services. The company’s AI initiatives encompass machine learning, natural language processing, and computer vision, enhancing productivity and user engagement. Microsoft’s research focuses on advancing conversational AI and integrating AI into various applications. Its AI capabilities support businesses with advanced tools for data analysis, automation, and enhanced user interactions.
  • Facebook: Facebook employs AI to improve user experiences, content moderation, and targeted advertising across its platforms, including Facebook, Instagram, and WhatsApp. The company’s AI Research (FAIR) division drives advancements in machine learning and computer vision. Facebook’s AI technologies power features like ad targeting and content recommendation, enhancing user engagement and platform efficiency. Additionally, the company’s AI innovations extend to its VR products, such as Oculus, expanding the scope of its digital offerings.
  • Apple: Apple integrates AI into its product ecosystem, including Siri for voice assistance, Face ID for facial recognition, and the Photos app for image processing. The company focuses on leveraging AI to improve user interactions and device functionality. Apple's AI-driven innovations extend to predictive text features and its Core ML framework for developers. The company's emphasis on AI reflects its commitment to advancing consumer electronics and software capabilities.
  • IBM: IBM is renowned for its AI contributions through the Watson platform, which offers a range of cognitive computing solutions. IBM’s AI applications span predictive analytics, natural language understanding, and enterprise AI solutions. The company’s AI technologies support diverse industries with advanced data analysis and business intelligence tools. IBM’s research and development efforts aim to drive innovation in cognitive computing and AI-powered business applications.
  • Tesla: Tesla harnesses AI for various aspects of its electric vehicles, including autonomous driving and energy efficiency. The company develops proprietary AI hardware and software for its Autopilot and Full Self-Driving (FSD) systems. Tesla’s AI technologies focus on enhancing vehicle navigation, predictive maintenance, and overall driving experience. The company’s commitment to AI innovation is central to its vision of autonomous transportation and sustainable energy solutions.
  • Netflix: Netflix utilizes AI and machine learning to tailor content recommendations and improve streaming quality for its users. The company’s AI algorithms analyze viewer behaviour to enhance content discovery and engagement on its platform. Netflix invests in AI research to refine its recommendation systems and optimize user experience. The use of AI helps Netflix maintain its competitive edge in the streaming industry by delivering personalized and high-quality content.
  • Uber: Uber applies AI to optimize its ride-sharing service, dynamic pricing, and route planning. The company’s AI-driven approach enhances operational efficiency and ensures accurate driver allocation and ride matching. Uber’s AI initiatives include predictive analytics for improved safety and reliability in urban mobility. The company’s commitment to AI technology supports its goal of transforming transportation and logistics.
  • Salesforce: Salesforce incorporates AI into its CRM platform through Einstein AI, offering features like predictive analytics, automated lead scoring, and personalized insights. The AI tools are designed to enhance sales, marketing, and customer service functions. Salesforce’s AI capabilities help businesses leverage data for more effective decision-making and customer interactions. The integration of AI in Salesforce’s platform supports streamlined processes and improved client engagement.

Career Development Paths in Artificial Intelligence

  • Machine Learning Engineer: Machine learning engineers are responsible for designing, implementing, and deploying machine learning models tailored to specific business challenges. They collaborate with data scientists and industry experts to develop predictive models, recommendation engines, and pattern recognition algorithms. Their role involves selecting appropriate machine-learning techniques and optimizing model performance for practical use.
  • Data Scientist: Data scientists work with large and complex datasets to extract meaningful insights and identify trends that drive strategic decisions. They employ statistical methods, machine learning techniques, and data visualization tools to analyze data and build predictive models. Their expertise enables them to forecast trends, optimize processes, and support decision-making through actionable insights.
  • Deep Learning Engineer: Deep learning engineers focus on creating and refining deep neural networks for applications like image and speech recognition, as well as natural language processing. They utilize frameworks such as TensorFlow, PyTorch, and Keras to design and train models on extensive datasets. Their work involves tuning model parameters, handling large-scale data, and ensuring that deep learning systems achieve high accuracy and efficiency.
  • Computer Vision Engineer: Computer vision engineers develop algorithms and systems to analyze and interpret visual data from images and video feeds. They work on technologies such as object detection, facial recognition, and image segmentation, often employing convolutional neural networks (CNNs) and advanced image processing techniques. Their efforts are essential in applications like autonomous vehicles, security systems, and medical imaging.
  • Natural Language Processing (NLP) Engineer: NLP engineers specialize in enabling machines to understand and process human language through advanced computational techniques. They work on applications including text classification, sentiment analysis, machine translation, and conversational agents like chatbots. Utilizing tools such as NLTK, SpaCy, and Transformer models, they design systems that can comprehend and generate natural language.
  • AI Research Scientist: AI research scientists focus on pioneering new algorithms, models, and techniques in artificial intelligence to drive advancements in the field. They conduct experimental research, publish their findings in academic journals, and contribute to the development of innovative AI technologies. Their role involves staying abreast of the latest developments, collaborating with academic and industry experts, and exploring novel approaches to push the boundaries of AI capabilities.
  • AI Product Manager: AI product managers oversee the development and launch of AI-driven products, ensuring they meet market needs and business objectives. They define product vision and requirements, prioritize features based on customer feedback, and coordinate with cross-functional teams to deliver effective AI solutions. Their role involves managing the product lifecycle from conception to deployment and ensuring the alignment of AI technology with strategic goals.
  • AI Consultant: AI consultants offer expert guidance to organizations seeking to implement AI technologies and integrate them into their operations. They assess organizational needs, evaluate potential AI solutions, and design strategies for adopting AI that align with business goals. Their role includes advising on technology choices, overseeing implementation, and facilitating digital transformation through AI.
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Artificial Intelligence Training Objectives

To join an Artificial Intelligence course, you should have a basic understanding of programming and data analysis. Familiarity with fundamental algorithms and statistics is advantageous. A keen interest in AI technologies and problem-solving techniques will further enrich your learning experience.
This course is perfect for individuals looking to deepen their knowledge of AI technologies and applications. It is especially suited for data scientists, software engineers, and business analysts seeking to specialize in machine learning and AI solutions.
Learnovita’s AI training includes an array of resources, such as detailed course materials, interactive modules, and practical projects. Participants benefit from expert-led sessions and hands-on exercises that enhance their understanding of AI principles and techniques.
  • Financial Services
  • Healthcare
  • Technology
  • Retail
  • Automotive
Yes, the AI course offers substantial hands-on experience through practical projects and real-world applications. You will build and deploy AI models, analyze datasets, and address complex challenges, gaining critical skills for effective AI practice.
  • Data Scientist
  • Machine Learning Engineer
  • AI Research Scientist
  • AI Product Manager
  • Business Intelligence Analyst
Our AI course offers extensive training and practical experience in artificial intelligence, complemented by a 100% placement guarantee. This ensures that, while the course significantly boosts your skills and job readiness, you will receive dedicated support to secure a role in the industry.
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Keras
  • Jupyter Notebook
Enrolling in Learnovita’s AI course will give you advanced expertise in artificial intelligence and machine learning. The course equips you with the skills to create innovative AI solutions, offering a competitive edge in the fast-paced tech industry.
  • Basics of Artificial Intelligence
  • Machine Learning Techniques
  • Deep Learning and Neural Networks
  • Data Preparation and Analysis
  • Deployment and Optimization of AI Models
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Artificial Intelligence Course Benefits

An Artificial Intelligence Certification Course in Hyderabad is designed to equip students to design smart systems, automate workflows, and solve complex problems based on data. Artificial Intelligence Internship in Hyderabad, machine learning, and data science professions. Students get Artificial Intelligence Projects in Hyderabad that make them work-ready and capable of driving transformation in many industries including manufacturing, finance and technology.

  • Designation
  • Annual Salary
    Hiring Companies
  • 4.54L
    Min
  • 6.97L
    Average
  • 13.0L
    Max
  • 4.7L
    Min
  • 7.5L
    Average
  • 13.5L
    Max
  • 4.9L
    Min
  • 8.1L
    Average
  • 14.0L
    Max
  • 5.24L
    Min
  • 8.5L
    Average
  • 14.5L
    Max

About Artificial Intelligence Certification Training

Our Artificial Intelligence Training in Hyderabad is designed to hone your skills from the ground up with a focus on real-world application. Learn AI fundamentals, machine learning, and model deployment through experiential learning. Backed by 500+ hiring partners, we offer Artificial Intelligence Course With Placement, helping you find top roles in a rapidly changing tech-driven industry.

Top Skills You Will Gain
  • Machine Learning
  • Deep Learning
  • Data Analysis
  • Neural Networks
  • Natural Language
  • Computer Vision
  • Statistical Modeling
  • Predictive Analytics

12+ Artificial Intelligence Tools

Online Classroom Batches Preferred

Weekdays (Mon - Fri)
17 - Nov - 2025
08:00 AM (IST)
Weekdays (Mon - Fri)
19 - Nov - 2025
08:00 AM (IST)
Weekend (Sat)
22 - Nov - 2025
11:00 AM (IST)
Weekend (Sun)
23 - Nov - 2025
11:00 AM (IST)
Can't find a batch you were looking for?
₹18000 ₹14500 10% OFF Expires in

No Interest Financing start at ₹ 5000 / month

Corporate Training

  • Customized Learning
  • Enterprise Grade Learning Management System (LMS)
  • 24x7 Support
  • Enterprise Grade Reporting

Why Artificial Intelligence Course From Learnovita ? 100% Money Back Guarantee

Artificial Intelligence Course Curriculum

Trainers Profile

At Learnovita, our Artificial Intelligence course is taught by certified professionals with extensive industry experience who are currently working at prestigious multinational corporations. With real-world insights and hands-on expertise, our trainers provide a comprehensive learning experience that bridges the gap between theoretical concepts and practical application, preparing students for successful AI careers.

Syllabus of Artificial Intelligence Course Download syllabus

  • Expertise in procedural and OOP
  • Setting up Python and IDEs
  • Skilled in Jupyter Notebook
  • Identifiers, indentation, and comments
  • Python data types and operators
  • Knowledge of Python loop types
  • Essential Python Skills
  • Setting Up Python Environment
  • Data Types in Python
  • Looping and Control Structures
  • Principles of Object-Oriented Programming
  • Connecting to Databases
  • Data Collection
  • Data Cleaning and Preparation
  • Data Transformation and Quality Assurance
  • Processing Text Data
  • Introduction to Big Data
  • Big Data Technologies (Spark, Hadoop, NoSQL)
  • Functions in SAS
  • Operators Used in SAS
  • Procedures in SAS
  • Creating Graphs with SAS
  • Using Macros in SAS
  • Formatting Data with SAS
  • Simple Linear Regression
  • Multiple Linear Regression Analysis
  • Non-Linear Regression Models
  • Forecasting Methods
  • Machine Learning Fundamentals
  • Clustering Techniques
  • Classification Methods
  • Association Rule Mining
  • Foundations of AI
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Natural Language Processing (NLP)
  • Generative Adversarial Networks (GANs)
  • Deep Learning Frameworks
  • Keras Application Programming Interface (API)
  • TensorFlow Platform
  • Deep Learning Techniques
  • Parallel and Distributed Computing
  • Deployment of Deep Learning Models
  • Reinforcement Learning Techniques
  • Image Generation with Neural Style Transfer
  • Object Detection Using CNN
  • Overview of Cloud Computing and AWS
  • Elastic Compute and Storage Volumes
  • Virtual Private Cloud (VPC)
  • Amazon Simple Storage Service (S3)
  • AWS Lambda and Amazon ML
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Need customized curriculum?

Industry Projects

Project 1
Predictive Maintenance for Equipment

AI-driven algorithms examine sensor data from machinery to forecast potential malfunctions before they arise. This foresight minimizes downtime and maintenance expenses by addressing problems in advance.

Project 2
Personalized Recommendations for E-Commerce

Machine learning algorithms evaluate user behaviour and preferences to deliver customized product recommendations. This tailored approach enhances the shopping experience and drives sales by presenting users with relevant options.

Project 3
Fraud Detection in Financial Transactions

AI technologies analyze historical transaction data to detect irregular patterns that may signal fraudulent activities. These systems assist financial institutions in thwarting fraud and safeguarding user finances throughout this process.

Career Support

Our Hiring Partner

Exam & Artificial Intelligence Certification

  • Machine Learning Engineer
  • Data Scientist
  • AI Research Scientist
  • AI Software Developer
  • Data Analyst
  • Achieving AI certification from Learnovita demonstrates your expertise in artificial intelligence technologies and their applications, which is highly esteemed in the technology sector.
  • This certification can open up numerous opportunities in fields such as data science, machine learning engineering, and AI research.
  • With Learnovita’s comprehensive career support and placement services, you'll be well-prepared to advance your career and explore new roles in AI-driven industries.
To pursue AI certification, it is beneficial to have a strong grasp of fundamental programming and data analysis. A background in machine learning concepts and statistical methods will aid in your preparation. Familiarity with core algorithms and data manipulation techniques will further enhance your learning process.
Yes, Learnovita’s AI training program offers a range of practice tests designed to refine your skills. These assessments focus on critical topics such as machine learning algorithms, data analytics, and model development, ensuring thorough preparation for the certification exam. Regular practice and in-depth feedback will help you effectively apply your knowledge in practical scenarios.
Earning Learnovita's AI certification provides significant advantages for professionals aspiring to excel in artificial intelligence. It equips you with advanced skills in AI technologies and their practical applications, establishing you as an expert in the field. This certification enhances your professional standing and opens up various career paths in AI and data science.

Our Student Successful Story

checkimage Regular 1:1 Mentorship From Industry Experts checkimage Live Classes checkimage Career Support

How are the Artificial Intelligence Course with LearnoVita Different?

Feature

LearnoVita

Other Institutes

Affordable Fees

Competitive Pricing With Flexible Payment Options.

Higher Artificial Intelligence Fees With Limited Payment Options.

Live Class From ( Industry Expert)

Well Experienced Trainer From a Relevant Field With Practical Artificial Intelligence Training

Theoretical Class With Limited Practical

Updated Syllabus

Updated and Industry-relevant Artificial Intelligence Course Curriculum With Hands-on Learning.

Outdated Curriculum With Limited Practical Training.

Hands-on projects

Real-world Artificial Intelligence Projects With Live Case Studies and Collaboration With Companies.

Basic Projects With Limited Real-world Application.

Certification

Industry-recognized Artificial Intelligence Certifications With Global Validity.

Basic Artificial Intelligence Certifications With Limited Recognition.

Placement Support

Strong Placement Support With Tie-ups With Top Companies and Mock Interviews.

Basic Placement Support

Industry Partnerships

Strong Ties With Top Tech Companies for Internships and Placements

No Partnerships, Limited Opportunities

Batch Size

Small Batch Sizes for Personalized Attention.

Large Batch Sizes With Limited Individual Focus.

Additional Features

Lifetime Access to Artificial Intelligence Course Materials, Alumni Network, and Hackathons.

No Additional Features or Perks.

Training Support

Dedicated Mentors, 24/7 Doubt Resolution, and Personalized Guidance.

Limited Mentor Support and No After-hours Assistance.

Artificial Intelligence Course FAQ's

Certainly, you are welcome to join the demo session. However, due to our commitment to maintaining high-quality standards, we limit the number of participants in live sessions. Therefore, participation in a live class without enrollment is not feasible. If you're unable to attend, you can review our pre-recorded session featuring the same trainer. This will provide you with a comprehensive understanding of our class structure, instructor quality, and level of interaction.
All of our instructors are employed professionals in the industry who work for prestigious companies and have a minimum of 9 to 12 years of significant IT field experience. A great learning experience is provided by all of these knowledgeable people at LearnoVita.
  • LearnoVita is dedicated to assisting job seekers in seeking, connecting, and achieving success, while also ensuring employers are delighted with the ideal candidates.
  • Upon successful completion of a career course with LearnoVita, you may qualify for job placement assistance. We offer 100% placement assistance and maintain strong relationships with over 650 top MNCs.
  • Our Placement Cell aids students in securing interviews with major companies such as Oracle, HP, Wipro, Accenture, Google, IBM, Tech Mahindra, Amazon, CTS, TCS, HCL, Infosys, MindTree, and MPhasis, among others.
  • LearnoVita has a legendary reputation for placing students, as evidenced by our Placed Students' List on our website. Last year alone, over 5400 students were placed in India and globally.
  • We conduct development sessions, including mock interviews and presentation skills training, to prepare students for challenging interview situations with confidence. With an 85% placement record, our Placement Cell continues to support you until you secure a position with a better MNC.
  • Please visit your student's portal for free access to job openings, study materials, videos, recorded sections, and top MNC interview questions.
LearnoVita Certification is awarded upon course completion and is recognized by all of the world's leading global corporations. LearnoVita are the exclusive authorized Oracle, Microsoft, Pearson Vue, and PSI exam centers, as well as an authorized partner of AWS. Additionally, those who want to pass the National Authorized Certificate in a specialized IT domain can get assistance from LearnoVita's technical experts.
As part of the training program, LearnoVita provides you with the most recent, pertinent, and valuable real-world projects. Every program includes several projects that rigorously assess your knowledge, abilities, and real-world experience to ensure you are fully prepared for the workforce. Your abilities will be equivalent to six months of demanding industry experience once the tasks are completed.
At LearnoVita, participants can choose from instructor-led online training, self-paced training, classroom sessions, one-to-one training, fast-track programs, customized training, and online training options. Each mode is designed to provide flexibility and convenience to learners, allowing them to select the format that best suits their needs. With a range of training options available, participants can select the mode that aligns with their learning style, schedule, and career goals to excel in Artificial Intelligence.
LearnoVita guarantees that you won't miss any topics or modules. You have three options to catch up we'll reschedule classes to suit your schedule within the course duration, provide access to online class presentations and recordings, or allow you to attend the missed session in another live batch.
Please don't hesitate to reach out to us at contact@learnovita.com if you have any questions or need further clarification.
To enroll in the Artificial Intelligence Course at LearnoVita, you can conveniently register through our website or visit any of our branches in India for direct assistance.
Yes, after you've enrolled, you will have lifetime access to the student portal's study materials, videos, and top MNC interview questions.
At LearnoVita, we prioritize individual attention for students, ensuring they can clarify doubts on complex topics and gain a richer understanding through interactions with instructors and peers. To facilitate this, we limit the size of each Artificial Intelligence batch to 5 or 6 members.
The average annual salary for Artificial Intelligence Professionals in India is 5 LPA to 8 LPA.
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