Online or onsite, instructor-led live Explainable AI (XAI) training courses demonstrate through interactive hands-on practice how to use explainable AI techniques to interpret, understand, and communicate the decision-making processes of AI models, enhancing transparency and trust in AI systems.
Explainable Artificial Intelligence (XAI) training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Explainable AI (XAI) training can be carried out locally on customer premises in Barranquilla or in NobleProg corporate training centers in Barranquilla.
NobleProg -- Your Local Training Provider
Barranquilla - Buro 51
Calle 94 #51B-43, Barranquilla, colombia
Buro 51 is a first class mix use complex which incorporates a class “A” office building and a 4 star Movich Hotel. Ground floor offers a variety of retail shops and amenities, and the building offeres unobstructed views of Barranquilla.
The center is located in Buenavista Trade Area, which is the most upscale and exclusive of the city with easy access to main highways to the international airport and port. Offers:
Fully equipped offices, ready to start working
Meeting rooms and videoconferencing studio
Regus IT high speed internet access
Administrative support on request
Major transport link - City/town center
Break-out areas
Elevate your presence with distinction at this prestigious office space situated in an enviable locale nestled between downtown and the Magdalena River. Green Towers boasts proximity to local enterprises and major banks, with convenient access to bus stops for seamless commuting.
This instructor-led, live training in Barranquilla (online or onsite) is aimed at intermediate-level professionals who wish to apply Explainable AI techniques to ensure fairness, transparency, and ethical AI systems.
By the end of this training, participants will be able to:
Understand the role of XAI in ethical AI systems.
Implement XAI techniques to detect and mitigate bias in AI models.
Ensure transparency in AI model decision-making processes.
Align AI development with ethical and regulatory standards.
This instructor-led, live training in Barranquilla (online or onsite) is aimed at advanced-level professionals who wish to explore state-of-the-art XAI techniques for deep learning models, with a focus on building interpretable AI systems.
By the end of this training, participants will be able to:
Understand the challenges of explainability in deep learning.
Implement advanced XAI techniques for neural networks.
Interpret decisions made by deep learning models.
Evaluate the trade-offs between performance and transparency.
This instructor-led, live training in Barranquilla (online or onsite) is aimed at advanced-level professionals who wish to enhance their understanding of XAI techniques for complex AI models.
By the end of this training, participants will be able to:
Implement state-of-the-art XAI techniques in AI models.
Interpret deep learning models and their decisions.
Apply advanced model-agnostic and model-specific explainability methods.
Address challenges related to AI transparency in complex systems.
This instructor-led, live training in Barranquilla (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to implement transparent AI systems in real-world applications.
By the end of this training, participants will be able to:
Understand the importance of transparency in AI models.
Implement advanced XAI techniques to interpret complex models.
Enhance model transparency using SHAP, LIME, and other tools.
Address ethical concerns and fairness in AI models.
This instructor-led, live training in Barranquilla (online or onsite) is aimed at beginner-level professionals who wish to learn the basics of Explainable AI and its role in developing responsible AI systems.
By the end of this training, participants will be able to:
Understand the fundamental concepts of Explainable AI.
Explore the importance of transparency and interpretability in AI models.
Learn basic techniques for making AI models explainable.
Apply XAI techniques to simple machine learning models.
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