AI-DL.AW1
Artificial Intelligence and Deep Learning for Decision Makers
AI isn’t a tough nut to crack. Let our course be the bridge between you and the AI-driven future.
- Practice in 17 Laboratorios prácticos — nothing to install
- 10 Lecciones interactivas y 62 topics mapped to the official exam objectives
Intermediate A tu propio ritmo · 1 año de acceso
17 LiveLabs prácticos
Practice real IT tasks in guided environments.
- Entornos reales
- Calificación automática
- Sin instalación
01 / Habilidades que obtendrás
What you will be able to do
Prepare to lead in the age of AI with Artificial Intelligence and Deep Learning for Decision Makers training course.
Through clear, structured lessons, you’ll explore the fundamentals of Artificial Intelligence (AI) and Deep Learning (DL), learn to implement models using Python, and analyze results for smarter decision-making.
This online course dives into the strategies of tech giants like Google, IBM, and Microsoft, showing you how AI and DL are transforming industries. From improving business operations to developing innovative products, you’ll gain actionable insights to apply in your organization.
So, gear up because the future of intelligent decision-making awaits you!
- Understand the core concepts of AI and DL and how they differ from traditional machine learning.
- Implement and analyze AI and DL models using industry-leading Python packages for real-world datasets.
- Apply algorithmic problem-solving approaches to design and develop intelligent systems for business challenges.
- Evaluate the business models and strategies of tech giants like Google, IBM, and Microsoft to integrate AI into organizational processes.
- Leverage cognitive learning services like IBM Watson and cloud computing intelligence to improve decision-making and operational efficiency.
- Design knowledge representation techniques to solve complex problems and enhance business outcomes.
- Explore the potential of AI and DL to innovate products, services, and customer experiences across industries.
Course Highlights
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10 Lecciones estructuradas Cobertura completa de los objetivos principales del curso
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17 LiveLabs prácticos Escenarios interactivos guiados con evaluación instantánea
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1 año de acceso completo Aprendizaje a tu propio ritmo, accesible en cualquier momento y en todos los dispositivos
02 / Lecciones y laboratorios
See exactly what you will learn and practice
Plan de estudios
10 Lecciones interactivas · 62 topics01 Preface +
02 Artificial Intelligence and Deep Learning 7 topics · 2 Laboratorio en vivo +
- Artificial Intelligence (AI)
- Deep Learning (DL)
- Machine learning versus deep learning
- Introduction to Artificial Neural Networks (ANNs)
- Algorithmic problem-solving approach
- Conclusion
- Questions
2 Laboratorio en vivo in this lesson — see the labs panel →
03 Data Science for Business Analysis 9 topics · 2 Laboratorio en vivo +
- What is data science?
- Challenges faced by businesses
- Problems that Occur During Model Development
- Problems Faced by IT Organizations While Developing Models
- Artificial Intelligence and Deep Learning Methods to Develop Models
- Improvements in the Business
- Benefits of data science in business analysis
- Conclusion
- Questions
2 Laboratorio en vivo in this lesson — see the labs panel →
04 Decision Making 6 topics · 2 Laboratorio en vivo +
- Representation Of Problems
- Design and development knowledge representation
- Representation techniques
- Knowledge Representation Issues
- Conclusion
- Questions
2 Laboratorio en vivo in this lesson — see the labs panel →
05 Intelligent Computing Strategies by Google 6 topics · 2 Laboratorio en vivo +
- The Strategies Of Google In Deep Learning Exploration
- Research Environment By Deepmind And Other Services Provided To The Users
- Business Models Currently Adopted by Google
- Google business model canvas
- Conclusion
- Questions
2 Laboratorio en vivo in this lesson — see the labs panel →
06 Cognitive Learning Services in IBM Watson 6 topics · 2 Laboratorio en vivo +
- The Cognitive Learning in NLP
- IBM Watson
- Improving services with IBM Watson
- How to impact businesses with IBM Watson
- Conclusion
- Questions
2 Laboratorio en vivo in this lesson — see the labs panel →
07 Advancement of Web Services by Baidu 5 topics · 2 Laboratorio en vivo +
- Baidu web services and its business orientation
- Deep Learning in Baidu Web Services
- Next steps of Baidu intelligent web services
- Conclusion
- Questions
2 Laboratorio en vivo in this lesson — see the labs panel →
08 Improved Social Business by Facebook 8 topics · 2 Laboratorio en vivo +
- Introduction
- Introduction to Facebook
- The Current Progress of FAIR for Advancing Social Media
- Application of AI in the Field at Facebook Scale
- Social Media Analytics
- Potential Use of DL in Improving Customers Among Social Media Users
- Conclusion
- Questions
2 Laboratorio en vivo in this lesson — see the labs panel →
09 Personalized Intelligent Computing by Apple 6 topics · 1 Laboratorio en vivo +
- Introduction to Apple
- AI in Apple: From Siri to the image processing
- Innovation On Intelligent Product Development
- Emergence Of Apple Products Year By Year
- Conclusion
- Questions
1 Laboratorio en vivo in this lesson — see the labs panel →
10 Cloud Computing Intelligence by Microsoft 9 topics · 2 Laboratorio en vivo +
- Objective
- Introduction
- Microsoft Approach to AI
- Microsoft AI platform - Overview
- Incorporation of DL capabilities in cloud computing
- Microsoft business model
- Microsoft business segments
- Conclusion
- Questions
2 Laboratorio en vivo in this lesson — see the labs panel →
Laboratorios prácticos Our edge
17 Laboratorio en vivos- Exploring AI and DL Foundations
- Implementing an Algorithmic AI Solution
- Developing AI Models for Business Problems
- Leveraging Data Science and AI for Business Challenges
- Modeling Decision-Making Using Decision Trees
- Structuring Problems and Knowledge for Intelligent Systems
- Simulating an Intelligent Search Ranking System
- Exploring Google's DL Innovations and Business Integration
- Analyzing Customer Sentiment Using NLP Techniques
- Leveraging Cognitive Computing and NLP with IBM Watson
- Generating Personalized Recommendations Using Similarity Matching
- Leveraging Baidu AI and DL in Web Services
- Analyzing Social Media Trends and Engagement Patterns
- Using Facebook AI for Social Media Analytics
- Exploring Apple AI and Innovation
- Simulating a Cloud-Based AI Prediction Service
- Exploring Microsoft AI and Cloud Innovation
03 / Preguntas frecuentes
Preguntas antes de empezar
Who is this course for?+
Do I need prior technical knowledge to enroll?+
Can I apply the learnings directly to my business?+
What tools or software will I need for this course?+
You’ll need access to a computer and a Wi-Fi connection. To use basic software like Python (with libraries such as TensorFlow or PyTorch), we recommend attempting our hands-on virtual labs. Detailed instructions will be provided.
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- 1 año de acceso completo
- 17 LiveLab incluido
- Certificado de finalización
No se requiere tarjeta de crédito