Artificial Intelligence Course in Jaya Nagar

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  • 362+ Hiring Companies & 13409+ Skilled Learners.
  • Learn AI from a Professional with over 12 years of experience.
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Hands On   40+ Hrs
Projects   4 +
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Artificial Intelligence Training Curriculum

Curriculum Designed By Experts

Expertly designed curriculum for future-ready professionals.

Industry Oriented Curriculam

An exhaustive curriculum designed by our industry experts which will help you to get placed in your dream IT company

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    30+  Case Studies & Projects
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    9+  Engaging Projects
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    10+   Years Of Experience
  • Definition and Scope
  • History and Evolution
  • Types of AI
  • AI Applications
  • Ethical Considerations
  • AI Development Tools
  • Introduction to Machine Learning
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
  • Model Evaluation
  • Feature Engineering
  • Neural Networks Overview
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Deep Learning Frameworks
  • Training Deep Learning Models
  • Transfer Learning
  • Introduction to NLP
  • Text Preprocessing
  • Text Representation
  • NLP Applications
  • Sentiment Analysis
  • Named Entity Recognition (NER)
  • Introduction to Computer Vision
  • Image Preprocessing
  • Object Detection
  • Image Segmentation
  • Face Recognition
  • Image Generation
  • Introduction to Reinforcement Learning
  • Markov Decision Processes (MDPs)
  • Q-Learning
  • Deep Q-Networks (DQN)
  • Policy Gradient Methods
  • Applications of Reinforcement Learning
  • Understanding AI Bias
  • Ethical Frameworks
  • Fairness and Accountability
  • Privacy and Security
  • Bias Mitigation Techniques
  • Regulatory Landscape
  • Introduction to Robotics
  • Robot Perception
  • Motion Planning
  • Robot Control
  • Human-Robot Interaction
  • Autonomous Systems
  • AI in Medical Imaging
  • Predictive Analytics in Healthcare
  • Drug Discovery and Development
  • Personalized Medicine
  • Telemedicine
  • Ethical Issues in AI Healthcare
  • AI in Business Strategy
  • Predictive Analytics in Finance
  • Algorithmic Trading
  • Customer Relationship Management (CRM)
  • Supply Chain Optimization
  • Risk Management

  • Adaptive Learning Systems
  • Intelligent Tutoring Systems
  • Educational Data Mining
  • Personalized Learning
  • Gamification
  • Future Trends in AI Education
  • Show More

    Artificial Intelligence Training Projects

    Become a Artificial Intelligence Expert With Practical and Engaging Projects.

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      Practice essential Tools
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      Designed by Industry experts
    •  
      Get Real-world Experience

    Chatbot

    Create a easy rule-based totally chatbot which could answer simple user questions with pre-defined answers.

    Image Classification

    Use a dataset inclusive of CIFAR-10 to educate a version that could classify snap shots into exclusive classes.

    Sentiment Analysis

    Analyze a social media publish or movie evaluate to see if the sentiment is positive, negative, or impartial.

    Recommendation System

    Create a cooperative filtering recommendation system that makes product or movie recommendations based on user tastes.

    Text Summarizer with (NLP)

    Develop a technology that extracts important sentences from papers or articles to summarize them.

    Voice Assistant

    Construct a basic, voice-activated helper that can do things like deliver the weather report and create reminders.

    Transfer Learning for Medical Image Diagnosis

    The use of transfer learning to categorize medical pictures, such as X-rays, using pre-trained models is the basis for medical image diagnosis.

    Conversational Understanding Chatbot Driven by AI

    Create a sophisticated chatbot that can carry on a dialogue by utilizing transformers to comprehend context.

    Emotion Recognition from Speech

    Build a model that examines audio data to identify emotions based on voice pitch and tone in order to perform emotion recognition from speech.

    Key Features

    Practical Training

    Global Certifications

    Flexible Timing

    Trainer Support

    Study Material

    Placement Support

    Mock Interviews

    Resume Building

    Batch Schedule

    Weekdays Regular (Class 1Hr - 1:30Hrs) / Per Session

    • 17-Feb-2025 Starts Coming Monday ( Monday - Friday) 08:00 AM (IST)
    • 19-Feb-2025 Starts Coming Wednesday ( Monday - Friday) 10:00 AM (IST)

    Weekend Regular (Class 3Hrs) / Per Session

    • 22-Feb-2025 Starts Coming Saturday ( Saturday - Sunday) 10:00 AM (IST)

    Weekend Fast-track (Class 6Hrs - 7Hrs) / Per Session

    • 23-Feb-2025 Starts Coming Saturday ( Saturday - Sunday) 10:00 AM (IST)

    Enquiry Form

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    • Learning strategies that are appropriate and tailored to your company's requirements.
    • Live projects guided by instructors are a characteristic of the virtual learning environment.
    • The curriculum includes of full-day lectures, practical exercises, and case studies.

    Artificial Intelligence Training Overview

    Artificial Intelligence Programmer’s Potential Career Paths

    An AI programmer gets access to a wide range of exciting work prospects due to the growing need for artificial intelligence understanding across sectors. A prominent job route is machine learning engineering, which involves creating and implementing algorithms that enable computers to learn from data. Another option for a career in data science is to analyze and understand complex data to help make business decisions. An other job path for AI programmers is in Natural Language Processing (NLP), which focuses on building machines that can understand and create human language. For people who are interested in cutting edge technology, a career in robotics engineering offers the opportunity to work on task automation and machine intelligence integration. Furthermore, positions in AI research offer the opportunity to further understanding of fields like deep learning and neural networks.

    What Are the Requirements for an Artificial Intelligence Training?

    • Educational Background: Being able to enter the field of artificial intelligence requires having a good educational background. In computer science, mathematics, statistics, or a related field, a bachelor's degree is often required for the majority of jobs. Advanced positions sometimes require a master's or Ph.D., particularly those in research or specialized fields. Key theoretical knowledge and problem-solving abilities are imparted by this official schooling.
    • Programming Skills: Training with AI requires a foundational understanding of computer languages. Because of its huge library (including TensorFlow and PyTorch) and ease of use, Python is the most popular language for AI development. Java may be used to create reliable programs, while R is a helpful language for statistical research. Practices may more efficiently construct algorithms and create AI models when they are conversant with these languages.
    • Statistics and Mathematics: Programming artificial intelligence (AI) requires a strong foundation in mathematics and statistics. Calculus, which aids in optimization, probability, which forms the foundation of many machine learning models, and linear algebra, which is crucial for working with matrices and vectors, are all significant branches. Data analysis and enhanced model performance are made possible by these mathematical ideas for AI practitioners.
    • Familiarity with machine learning: Training with AI requires a fundamental understanding of machine learning. This includes understanding various methods and how they are used, such as choice trees, support vector machines, and neural networks, among others. Knowing how to select the right models depending on certain objectives and datasets is essential, as is having experience with both supervised and unsupervised learning approaches.
    • Hands-On Experience: When learning AI, real-world experience is crucial. Aspiring AI professionals may put their theoretical knowledge to use in practical settings by taking part in projects, internships, or open-source efforts. Creating a portfolio of work not only shows prospective employers what you are capable of, but it also improves your technical know-how and problem-solving capabilities.
    • Continuous Learning: Artificial intelligence is a constantly developing subject, thus lifelong learning is crucial. Remaining competitive for practitioners means keeping up with the newest developments through seminars, industry conferences, and online courses. Participating in AI groups and keeping up with research articles also encourages continuous learning and innovation, guaranteeing that knowledge and abilities stay applicable in a changing industry.

    Reasons to Consider Enrolling in Artificial Intelligence Training

    There are several strong benefits to taking artificial intelligence training, and they may greatly improve your skill set and employment opportunities.These skills put you in a position to take advantage of numerous lucrative career opportunities, since the need for AI professionals is growing in a number of areas, such as technology, healthcare, and finance. With artificial intelligence (AI), you may work on ground-breaking initiatives that have the potential to completely change the course of history. Furthermore, the multidisciplinary nature of AI means that you may apply the skills you learn to a variety of disciplines, which gives you flexibility in your career. Moreover, AI training improves your ability to solve problems by equipping you to take on challenging problems and find data-driven solutions. Last but not least, participating in AI projects enables you to make a significant contribution to developments that tackle important social concerns, making your job not just exciting but also impactful.

    What goals are achieved in a Artificial Intelligence Training?

    • Comprehending Fundamental Ideas: Participants have a strong understanding of fundamental AI concepts such computer vision, natural language processing, machine learning, and deep learning. This foundational knowledge is required to implement AI techniques correctly.
    • Gaining Expertise: Training gives people the ability to develop in languages such as Python and R and to become proficient in AI frameworks and libraries like PyTorch and TensorFlow. These abilities are necessary for developing and implementing AI models.
    • Knowledge Application in Practice: Trainees are assisted in applying academic knowledge to real-world problems through practical projects and real-world applications. Through hands-on interaction with AI tools and technologies, this experiential learning approach strengthens comprehension and cultivates problem-solving skills.
    • Expertise in Data Analysis: In order to create AI models that work, participants must first learn how to assess and preprocess data. This covers feature engineering, data cleansing, and data distribution understanding approaches.
    • Model Building and Assessment: The training process centers around the whole lifespan of AI model building, encompassing the steps of algorithm selection, model validation, training, and evaluation. This objective guarantees that learners can produce models that function effectively on problems in the actual world.
    • Morality and Sustaining AI Methods: A crucial component of AI education is comprehending the moral ramifications of AI technology and the significance of conscientious AI activities. Learners acquire the skills necessary to identify prejudice, maintain justice, and apply transparency in AI systems.

    Techniques and Trends in Artificial Intelligence Development

    The field of artificial intelligence development is always changing because of new methods and approaches that improve the technology's capabilities and uses. Transformer models have revolutionized natural language processing and are currently being used to diverse domains like as image recognition and generative tasks. This is one noteworthy development in the field. Reinforcement learning is becoming more popular because it helps robots and gaming AI since it allows systems to learn optimum actions through interaction with surroundings. Furthermore, explainable AI (XAI) is receiving greater attention. Its goal is to increase user comprehension and transparency of AI decision-making processes, hence resolving ethical issues and building user confidence.

    Add-Ons Info

    Career Opportunities  After Artificial Intelligence

    Machine Learning Engineer

    An artificial intelligence-based machine learning engineer creates and refines machine learning models and algorithms to evaluate massive datasets, enhance operational processes, and resolve challenging problems.

    Data Scientist

    Insights are extracted from organized and unstructured data using statistical approaches, machine learning, and data visualization. Creates predictive models and actionable suggestions to support organizational decision-making.

    AI Research Scientist

    Conducts cutting-edge artificial intelligence research, investigating novel algorithms, methodologies, and applications. To enhance AI technology, researchers publish their discoveries in academic publications and work with cross-functional teams.

    Computer Vision Engineer

    Computer vision engineer Creates algorithms and methods that help robots comprehend and analyze visual information from their surroundings. Worked on face recognition, self-driving cars, and augmented reality.

    NLP Engineer

    Focuses on developing systems that can both interpret and produce human language. develops software that enhance human-computer interaction, including chatbots, language interpreters.

    AI Product Manager

    AI Product Manager As you develop and deploy AI-driven solutions, make sure they meet consumer needs. collaborates with engineers, marketers, and designers to bring cutting-edge artificial intelligence solutions.


    Skill to Master
    Machine Learning Algorithms
    Neural Networks
    Natural Language Processing
    Computer Vision
    Data Analysis
    Programming (Python, R)
    Deep Learning
    AI Ethics
    Data Visualization
    Model Deployment
    Predictive Analytics
    Reinforcement Learning
    Show More

    Tools to Master
    TensorFlow
    PyTorch
    Keras
    Scikit-learn
    Jupyter Notebook
    IBM Watson
    Microsoft Azure Machine Learning
    Google Cloud AI Platform
    Amazon SageMaker
    OpenAI GPT
    RapidMiner
    H2O.ai
    Show More
    Our Instructor

    Learn from certified professionals who are currently working.

    instructor
    Training by

    Vikram , having 8 yrs of experience

    Specialized in: Artificial Intelligence Ethics, Explainable AI, Bias in AI, and AI Policy Development.

    Note: Vikram is an expert in the field of AI ethics, specializing on the effects of AI technology on society. His distinct viewpoint enhances the course as he pushes students to consider the ramifications of their AI work.

    Job Assistant Program

    We are proud to have participated in more than 40,000 career transfers globally.

    Artificial Intelligence Certification

    Certificate
    GET A SAMPLE CERTIFICATE
  • Skill Validation
  • Career Advancement
  • Networking Opportunities
  • Increased Earning Potential
  • Basic Programming Skills
  • Mathematics Knowledge
  • Data Handling Skills
  • Foundational AI Knowledge
  • Yes, employment is assured by a certification. Even while it increases your chances, market demand, experience, and talents all matter a lot.

    You may absolutely seek credentials in numerous Artificial Intelligence training! Many professionals make this decision in order to increase their knowledge and skill set in a variety of AI-related fields, including computer vision, natural language processing, and machine learning.

  • AI/ML Engineer
  • Data Scientist
  • AI Researcher
  • Business Analyst
  • Proctored Online Exams
  • Self-Paced Courses
  • Flexible Scheduling
  • Entry-Level Certifications
  • Intermediate and Advanced Certifications
  • Practical Experience
  • Career Goals
  • Industry Recognition
  • Curriculum Quality
  • Networking Opportunities
  • Return on Investment
  • Alternatives
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    Frequently Asked Questions

    • Absolutely, you may sign up for demo sessions offered by a lot of training providers, including ACTE, before committing to a course. You may explore the entire learning environment, course material, and teaching style during these demo sessions. It's an excellent method of determining whether the course fulfills your expectations and advances your learning objectives.
    • ACTE professors have vast experiences in their respective professions and are seasoned experts. They consist of recognized specialists, seasoned professionals, and industry experts with practical knowledge in data science, artificial intelligence, and related fields. To guarantee top-notch instruction, the instructors are chosen according to their areas of specialization, aptitude as teachers, and real-world experience.
    • Yes, once students finish their studies, ACTE usually helps them find jobs. This help might come in the form of interview coaching, résumé development, and job search aid. The objective is to help students make a seamless transition into the workforce by using ACTE's industry connections and career services.
    • After completing the Artificial Intelligence Training, you will receive a certification from ACTE attesting to your proficiency in the field. This qualification, which is recognized in the business, attests to your competence with AI concepts, tools, and procedures.
    • Yes, as part of their training at ACTE, students frequently work on real-world projects.
    • Working on real-world projects gives students real-world experience and teaches them how to apply their academic knowledge to real-world issues.
    • Acquire real-world experience
    • The purpose of these projects is to improve student learning results and get them ready for real-world AI issues.

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    • Flexibility: Online, weekends & more.
    • Hands-on: Projects & practical exercises.
    • Placement support: Resume & interview help.
    • Lifelong learning: Valuable & adaptable skills.
    • Full curriculum: Foundational & advanced concepts.

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