Course Provider
What will you learn in Artificial Intelligence Engineer (AIE) course?
Demonstrate what machine learning, deep learning, and neural networks are, as well as machine learning methods like classification, regression, clustering, and dimensional reduction.
- To address complex issues, use deep learning, machine learning, computer vision, and natural language processing.
- Creates AI models using deep learning neural networks and machine learning technologies to gain commercial insights.
- Machine learning models are used to create APIs.
- Internal stakeholders and product managers are being educated on the usefulness of the AI models they are developing.
- Create supervised and unsupervised machine learning models using SciPy and ScikitLearn.
- Build machine learning algorithms and pipelines using Apache Spark.
- Deep learning models and neural networks are created using Keras, PyTorch, and TensorFlow.
- Demonstrate what machine learning, deep learning, and neural networks are, as well as machine learning methods like classification, regression, clustering, and dimensional reduction.
- To address complex issues, use deep learning, machine learning, computer vision, and natural language processing.
- Creates AI models using deep learning neural networks and machine learning technologies to gain commercial insights.
- Machine learning models are used to create APIs.
- Internal stakeholders and product managers are being educated on the usefulness of the AI models they are developing.
- Create supervised and unsupervised machine learning models using SciPy and ScikitLearn.
- Build machine learning algorithms and pipelines using Apache Spark.
- Deep learning models and neural networks are created using Keras, PyTorch, and TensorFlow.
Artificial Intelligence Engineer (AIE)
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Skill Type
Emerging Tech -
Domain
AI/BDA -
Course Category
Deepskilling Course - Placement Assistance
Yes
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Certificate Earned Joint Co-Branded Participation Certificate & Partner Completion Certificate -
Nasscom assessment Coming Soon -
Course Covered under GoI Incentive
Yes -
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Course Price
INR 1,10,000+ 18% GST -
Course Duration
120 Hours
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Why you should take Artificial Intelligence Engineer (AIE) course?
AI Engineer is the most comprehensive course with Curriculum aligned with industry and accredited by IABAC®Mentors are PhDs., from Elite Universities with decades of experience in AI Internship from AI company is bundled with the course 1 client or startup project with Industry experts support Proven Track record of Job Assistance and Placement Service
Who should take Artificial Intelligence Engineer (AIE) course?
- Graduates and undergraduates who want to work in the field of artificial intelligence.
- IT specialists that specialize in the deployment of AI and ML on the cloud.
- Applicants who wish to strengthen their Machine Learning and Big Data skills and gain a leg up in Big Data Science.
- Professionals in the analytics industry who desire to pursue AI as a profession.
- Senior analysts and team leaders
Curriculum
- Course 1: Data Science Foundation
- Course 2: Python Essentials for Data Science
- Course 3: R Language Essentials
- Course 4: Math for Data Science
- Course 5: Statistics for Data Science
- Course 6: Data Preparation with Numpy & Pandas
- Course 7: Visualization with Python
- Course 8: Machine Learning Associate
- Course 9: Advanced Machine Learning
- Course 10: SQL for Data Science
- Course 11: Deep Learning – CNN Basics
- Course 12: Tableau Associate
- Course 13: ML Model Deploy- Flask API
- Course 14: Big Data Essentials
- Course 15: Data Science Project Execution
- Course 16: Artificial Intelligence Foundation
- Course 17: Machine Learning
- Course 18: Tensorflow 2.x Platform
- Course 19: Core Learning Algorithms
- Course 20: Understanding Neural Networks
- Course 21: Implementing Deep Neural Networks
- Course 22: Deep Computer Vision - CNN
- Course 23: Recurrent Neural Network (RNN)
- Course 24: Natural Language Processing
- Course 25: Reinforcement Learning Concepts
- Course 26: Implementing Reinforcement Learning
- Course 27: Generative Adversarial Network
Tools you will learn in Artificial Intelligence Engineer (AIE) course
- The artificial intelligence engineer course curriculum covers some of the most widely used artificial intelligence tools, including Python, Scikit Learn, TensorFlow, Theano, Keras, PyTorch, and CNTK.
- Candidates will be provided an in-depth understanding of the most popular and highly graded tools and software platforms extensively utilized for AI research and design.
FAQs
The trainers for the Artificial Intelligence Engineer course have experienced Data Scientists, AI and Machine Learning experts and AI practitioners delivering solutions for fortune 100 companies
Yes, Coding is required to learn Artificial Intelligence Engineer courses.
You can enroll for the Artificial Intelligence Engineer Course by visiting our website. Details of registered can be found in the course pages.
Yes. You will be given a certificate after the completion of the Artificial Intelligence Engineer course.
The course is a comprehensive program that delves into advanced AI techniques, including neural networks, deep learning, and more, to prepare you for AI engineering roles.
This course caters to individuals aspiring to become AI engineers, as well as professionals seeking to enhance their AI skillset.
The course encompasses advanced AI concepts, neural networks, deep learning architectures, model optimization, and practical implementation.
While no strict prerequisites are required, a basic understanding of programming and AI fundamentals can be beneficial.
The course includes interactive lessons, hands-on projects, assessments, and real-world applications to provide a comprehensive AI learning experience.