Artificial Intelligence Engineer
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Course Overview

The Artificial Intelligence Engineer course is a comprehensive training program that covers the fundamental theories, algorithms, and applications of AI. Through this course, you will learn about various AI technologies, such as machine learning, deep learning, natural language processing, computer vision, and more. You will also gain hands-on experience with popular AI tools and frameworks, enabling you to build intelligent systems and solve real-world problems.

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Artificial Intelligence Engineer
Artificial Intelligence Engineer Content

Overview of artificial intelligence History and evolution of AI Ethical considerations in AI

Supervised learning algorithms Unsupervised learning algorithms Model evaluation and selection

Neural network architecture and components Deep learning frameworks (e.g., TensorFlow, Keras) Convolutional neural networks and recurrent neural networks

Text preprocessing and feature extraction Sentiment analysis and text classification Language generation and machine translation

Image preprocessing and feature extraction Object detection and image segmentation Image classification and image generation

Markov decision processes Q-learning and policy gradients Applications of reinforcement learning

Bias and fairness in AI systems Privacy and security considerations Ethical frameworks for AI development and deployment

AI in healthcare, finance, and other industries Robotics and autonomous systems Emerging trends in AI research and development
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    Artificial Intelligence Engineer Projects

    Develop a machine learning model to classify emails as spam or non-spam.
    Perform feature engineering and train the model using a suitable algorithm.
    Evaluate the model's performance and deploy it for real-time email filtering.

    Build a deep learning model that generates descriptive captions for images.
    Utilize convolutional neural networks for image feature extraction.
    Combine image features with natural language processing techniques to generate captions.

    Analyze sentiment in social media posts to understand public opinion.
    Preprocess text data and use machine learning algorithms for sentiment classification.
    Visualize and interpret the sentiment analysis results for actionable insights.

    Develop an AI-based simulation environment for autonomous driving.
    Utilize reinforcement learning techniques to train an agent to navigate the simulation.
    Evaluate the agent's performance in different driving scenarios.

    Create a chatbot that can interact with users and provide relevant information.
    Use natural language processing techniques for text understanding and response generation.
    Train the chatbot using a conversational dataset and deploy it for real-time interactions.

    Big Data Hadoop Course Fee

    Preffered

    Online Classroom

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    Corporate Training
    • 36 hours of instructor-led online training
    • Flexibility to choose classes
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    All Our Programs Include

    This training course is designed to help you clear the Cloudera Spark and Hadoop Developer Certification (CCA175) exams.

    Real-world projects from industry experts

    With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.

    Technical mentor support support

    With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.

    Personal career coach and career services

    With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.

    Flexible learning program

    With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.

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    Artificial Intelligence Engineer Certification

    Student Reviews
    4.5   (1.2k)
    FAQ’s

    The prerequisites for this course include basic programming skills (preferably Python), knowledge of linear algebra and calculus, and familiarity with machine learning concepts.

    Yes, this course is suitable for beginners as well as experienced professionals. It covers the fundamental concepts and provides a gradual learning curve.

    Yes, this course involves coding. You will gain hands-on experience with programming in Python and implementing AI algorithms.

    Yes, you will have access to the course materials through our dedicated learning management system. You can access them online anytime, anywhere.

    Yes, upon successful completion of the course, you will receive a certificate that validates your skills as an Artificial Intelligence Engineer.

    Yes, you can interact with the instructors during the course through interactive sessions, discussion forums, and Q&A sessions.

    Yes, we provide career guidance to help you explore job opportunities in the field of AI. We also offer job placement support, including resume building and interview preparation.

    This course covers popular AI tools and frameworks such as TensorFlow, Keras, scikit-learn, and more.

    Yes, you can work on the projects at your own pace. However, it is recommended to follow the project timeline to stay on track with the course schedule.

    Yes, we offer financial assistance options, including scholarships and installment plans. Please contact our admissions team for more information.

    If you decide to switch to a different course within a specific timeframe, we can assist you with the transition. Please contact our support team for more details.

    While the emphasis is on individual projects, there may be opportunities for group projects to foster collaboration and teamwork.

    Yes, you will have lifetime access to the course materials even after completing the course. You can refer to them for future reference or to refresh your knowledge.

    The course offers flexible learning options, allowing you to study at your own pace. However, there may be suggested timelines and deadlines for better learning outcomes.

    We have a refund policy in place. Please refer to our refund policy for more information on eligibility and terms.

    Yes, you will have the option to download the course materials for offline access through our learning management system.

    Absolutely! The course projects are designed to simulate real-world scenarios, enabling you to apply the skills learned to practical AI projects.

    Yes, there will be assessments and exams throughout the course to evaluate your understanding and progress.

    Yes, our technical support team is available to assist you with any technical difficulties you may encounter during the course.

    To enroll in the course, simply visit our website and follow the instructions for enrollment. Our admissions team will guide you through the process and assist with any questions or concerns.

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    Online courses open the opportunity for learning to almost anyone, regardless of their scheduling commitments.

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