Artificial Intelligence Expert (AIE)
Artificial Intelligence (AI) is revolutionizing industries and transforming how we interact with technology—from web searches and speech recognition to self-driving cars and intelligent assistants. The Artificial Intelligence Expert (AIE) certification provides comprehensive training in machine learning, deep learning, and neural networks, enabling professionals to understand and build state-of-the-art AI solutions using tools like Python, TensorFlow, and Keras.
This course is designed to help you master both theoretical foundations and practical implementations in AI, preparing you to participate in the development of cutting-edge technologies in data science and intelligent systems.
ADDRESSED TO
This course is ideal for:
- Engineers and analysts
- Marketing managers interested in AI applications
- Data analysts, data scientists, and data stewards
- Professionals and students interested in data mining, machine learning, and deep learning
- Anyone looking to acquire solid AI foundations and practical skills in neural network development
PURPOSE
The purpose of this certification is to:
- Understand the core concepts of deep learning and its real-world impact
- Master the architecture and training of neural networks
- Learn how to implement machine learning pipelines and AI workflows
- Develop the ability to use tools like NumPy, pandas, scikit-learn, TensorFlow, and Keras
- Gain hands-on experience by completing guided AI projects and experiments
- Prepare for participating in AI competitions (e.g., Kaggle) and deploying intelligent systems
MAIN TOPICS
The course is structured in six learning modules:
I. Deep Learning Fundamentals
- Representing neural networks
- Nonlinear activation functions
- Hidden layers and architecture
- Guided Project: Building a handwritten digit classifier
II. Machine Learning Project
- Data cleaning and preprocessing
- Feature engineering and selection
- Making predictions and evaluating models
- Key takeaways for building successful ML pipelines
III. Kaggle Fundamentals
- Introduction to Kaggle competitions
- Feature preparation, selection, and engineering
- Model selection and hyperparameter tuning
- Guided Project: Creating a complete Kaggle workflow
IV. TensorFlow Concepts
- Introduction to TensorFlow framework
- Basics and structure of TensorFlow
- Building classification models with neural networks
- Linear regression implementation in TensorFlow
V. Keras Basis
- Overview of Keras and its layers
- Implementing deep learning projects with Keras
- Comparison: Keras vs TensorFlow
VI. References and Additional Resources
- Recommended readings, libraries, and AI development tools
Duration:
Duración:
Number of questions:
Minimum passing:
Available languages:
Second chance (free):
Take your exam online.
$150.00
