- Overview
- Course Details
- Syllabus
- FAQ
Become an AI Developer: Master Machine Learning, AI Frameworks, and Real-World Applications to Transform Your Career!
BEST INSTITUTE 4.9 Ratings
Elysium Academy brings you an advanced AI Engineering program crafted for developers aiming to build intelligent solutions. This course covers machine learning, deep learning, and neural networks through real-world projects. Learners will gain practical experience with industry-standard tools like TensorFlow, PyTorch, and OpenCV. By the end of the program, you will be ready to design, deploy, and optimize AI-powered applications effectively.
2.2
Version
90 Hours
Duration
44 Hours
Theory
46 Hours
Practical
- Industry-Oriented AI Projects
- Personalized Coordinator Support
- Continuous Trainer Feedback
- Trainer Availability After Sessions
- Globally Recognized AI Certification
- Hands-On Assignments with Real-World Data
- Expert-Led Workshops
- Fundamentals of AI, ML, and Neural Networks
- Implementation of AI algorithms in Python
- Hands-on experience with TensorFlow, PyTorch & OpenAI APIs
- Building, training, and deploying AI models
- AI ethics, bias, and data management principles
- Real-time AI project simulations and case studies
Top Companies Offer This Course to Their Employees
This course is trusted and selected by top-rated tech giants worldwide for AI-driven innovation.
The AI Engineering for Developers program equips learners with the skills to design, build, and deploy AI-driven applications. Dive into machine learning, natural language processing, computer vision, and neural networks with real-world projects. With expert guidance, you will master AI frameworks, tools, and coding practices. This course prepares developers to integrate AI seamlessly into applications for innovative solutions.
The AI Engineering for Developers course trains you to create intelligent applications using cutting-edge AI technologies. You will learn machine learning, deep learning, natural language processing, and model deployment while gaining proficiency with TensorFlow, PyTorch, and cloud-based AI platforms.
- AI engineering is one of the fastest-growing fields in technology
- Developers with AI skills are highly sought after across industries.
- AI is transforming sectors like healthcare, finance, and automation.
- Mastering AI tools boosts career growth and innovation potential.
- AI engineering forms the foundation for robotics and autonomous systems
AI Engineering for Developers Certification validates your expertise in designing AI-powered applications.
Our Training Program Benefits
- Live, interactive training by experts.
- Learner-focused and industry-relevant curriculum
- Challenge-based, hands-on projects.
- Opportunities for collaboration and teamwork.
- Cost-effective learning solutions
- Flexible and convenient training modes.
- Tailored curriculum for your career goals.
Chapter-1 : Introduction to AI Engineering
- What is Artificial Intelligence?
- AI vs. Machine Learning vs. Deep Learning
- Key Applications of AI in Modern Development
- AI Lifecycle and Workflow
- Tools and Frameworks for AI Engineers (TensorFlow, PyTorch, etc.)
Chapter-2 : Python for AI
- Python Basics for AI and Data Science
- Data Structures and Libraries (NumPy, Pandas)
- Data Visualization with Matplotlib and Seaborn
- Data Cleaning and Preprocessing Techniques
Chapter 3: Machine Learning Fundamentals
- Supervised vs. Unsupervised Learning
- Classification and Regression Models
- Model Training, Validation & Testing
- Feature Engineering and Selection
Chapter 4: Deep Learning & Neural Networks
- Introduction to Neural Networks
- Activation Functions and Optimizers
- Building Models with Keras and TensorFlow
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs) and LSTMs
Chapter 5: Natural Language Processing (NLP)
- Text Preprocessing and Tokenization
- Sentiment Analysis
- Named Entity Recognition (NER)
- Building Chatbots using NLP
Chapter 6: Computer Vision
- Image Processing Basics
- Object Detection and Recognition
- Face Detection using OpenCV
- Image Classification Projects
Chapter 7: AI Model Deployment
- Deploying AI Models with Flask/Django
- Using Cloud Platforms (AWS, GCP, Azure)
- Model Optimization and Scaling
Chapter 8: Real-World AI Projects
- End-to-End AI Project Implementation
- Best Practices in AI Development
- Capstone Project Presentation
What is AI Engineering for Developers?
AI Engineering for Developers is a program that teaches developers how to build, deploy, and optimize AI-powered applications using modern frameworks and tools.
Who can enroll in this AI Engineering course?
This course is ideal for software developers, data scientists, and IT professionals who want to master AI technologies like machine learning and deep learning.
What skills will I learn in AI Engineering?
You will learn Python for AI, machine learning algorithms, neural networks, natural language processing (NLP), computer vision, and AI model deployment.
Is coding experience required for this AI course?
Yes, basic knowledge of programming (preferably Python) is recommended, but we provide a crash course on Python essentials for AI.
What are the career opportunities after AI Engineering training?
You can work as an AI Engineer, Machine Learning Engineer, Data Scientist, or Deep Learning Specialist in top tech companies.
Do you provide real-time AI projects?
Yes, this course includes hands-on projects like chatbot creation, image recognition, and predictive analytics.
Is this AI course online or offline?
We offer both online and offline learning modes to suit your convenience.
Will I get a certificate after completing AI Engineering?
Yes, you will receive an industry-recognized AI Engineering for Developers certification.
How long does it take to complete this AI course?
The duration varies from 8 to 12 weeks, depending on the chosen learning schedule.
What tools and frameworks will I learn in this course?
You will gain expertise in TensorFlow, PyTorch, OpenCV, and cloud AI platforms like AWS and Google AI.
How is this AI Engineering course different from other AI courses?
Our course focuses on practical implementation with real-world projects and advanced AI model deployment techniques.
What is the average salary of an AI Engineer?
AI Engineers earn an average salary of ₹6–12 LPA in India, with top professionals earning even higher packages.
- AI Engineering For Developers
- Duration: 90 Hours
- Level: Beginner
- Days: 90 Days
- Chapters: 8
- Language: English
- Certifications: Yes
- Code: EAPL/PROF/PRTC35
- Course Code: EAPAP
- Sub Category: AI / ML Development
AI Engineering For Developers – Features
Learn the core principles of Artificial Intelligence, including machine learning, deep learning, and neural networks.
Work on real-world AI applications like chatbots, image recognition, and NLP-based solutions.
Master AI frameworks and libraries such as TensorFlow, PyTorch, and OpenCV for cutting-edge development.
Gain expertise in deploying AI models using cloud platforms like AWS, GCP, and Azure.
Enhance your coding abilities in Python with AI-focused projects and problem-solving exercises.
Understand AI ethics, scalability, and optimization for building robust, production-ready solutions.
What Will You Learn?
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