Artificial Intelligence Expert Certificate CAIEC
Duration: 2 Days
- Understand the fundamental keys of the deep
learning approach
- Master the theoretical and practical foundations of neural network architecture and convergence
- Represent different existing fundamental architectures and master fundamental
implementations
- Master methodologies for configuring neural networks, the strengths and limitations of existing tools and libraries (pandas, numpy, scikit-learn)
Engineers, analysts, marketing managers, data analysts, data scientists, data stewards, and anyone interested in data mining and machine learning techniques
There are no formal prerequisites for this certification.
I.1 Representing Neural Networks
I.2 Nonlinear Activation Functions
I.3 Hidden Layers
I.4 Guided Project: Building A Handwritten Digits Classifier
- Machine Learning Project
II.1 Machine Learning Project Walkthrough: Data Cleaning
II.2 Machine Learning Project Walkthrough: Preparing the Features
II.3 Machine Learning Project Walkthrough: Making Predictions
Key Points
Kaggle Fundamentals
III.1 Getting Started with Kaggle
III.2 Feature Preparation, Selection and Engineering
III.3 Model Selection and Tuning
III.4 Guided Project: Creating a Kaggle Workflow
- TensorFlow Concepts
IV.1 Presentation of TensorFlow
IV.2 TensorFlow Basics
IV.3 Classification of Neural Network in TensorFlow
IV.4 Linear Regression in TensorFlow
- Keras Basis
ARTIFICIAL INTELLIGENCE EXPERT CERTIFICATE CAIEC®
- Keras Basis
V.1 Kears Layers
V.2 Deep Learning with Keras Implementation and Example
V.3 Keras Vs Tensorflow – Difference Between Keras and Tensorflow
- References