Course Highlights
Following are Highlight of this course
- EXIN BCS AI Essentials global certification upon passing the exam.
- Flexible self-paced online learning for convenience.
- Gain a comprehensive understanding of AI concepts, including machine learning, neural networks, and natural language processing.
- Explore how AI is applied across industries, from automation and data analysis to customer service and predictive modeling.
- Enhances career prospects with in-demand AI skills.
- Comprehensive 40 hours of video lectures and reading materials.
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Nasscom Assessment
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Placement Assistance
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Course Details
What will you learn in EXIN BCS Artificial Intelligence Essentials - powered by CTPL.io?
- Understand the fundamentals of artificial and human intelligence, including their differences and the history of AI and machine learning.
- Learn core concepts such as machine learning, data science, hypothesis testing, and experimentation.
- Explore real-world applications of AI, focusing on its benefits, challenges, risks, and opportunities.
- Gain insights into the steps and requirements for implementing machine learning solutions effectively.
- Develop foundational knowledge of machine learning, including intelligent agents, neural networks, and data preparation.
- Apply machine learning models to solve real-world problems, validate their effectiveness, and optimize performance.
- Discover future possibilities of AI through collaboration between humans and machines, exploring emerging technologies.
- Acquire the skills necessary to implement AI-driven solutions and navigate advancements in the AI field.
Why you should take Complete Course on EXIN BCS Artificial Intelligence Essentials - powered by CTPL.io?
- Earn the EXIN BCS Artificial Intelligence Essentials, a globally recognized certification that enhances your professional credibility.
- Gain foundational knowledge of AI, enabling you to understand and contribute to AI-driven projects confidently.
- Learn about ethical and legal considerations, ensuring responsible AI usage in real-world applications.
- Understand key AI concepts like machine learning, data management, and generative AI for practical implementation.
- Explore opportunities for integrating AI into organizational processes for better decision-making and innovation.
- Build a solid foundation in AI that can be applied across various industries and professional roles.
- Develop the skills to address AI-related risks, costs, and benefits through structured project management.
- Prepare for future-ready careers in technology with industry-relevant knowledge and certification.
Who should take Complete Course on EXIN BCS Artificial Intelligence Essentials - powered by CTPL.io?
- IT Professionals seeking to enhance their knowledge of Artificial Intelligence and its applications.
- Business Leaders aiming to leverage AI for strategic decision-making and innovation in their organizations.
- Students and Graduates looking to gain a globally recognized AI certification and build a future-ready skill set.
- Project Managers interested in understanding AI project management, including risks, costs, and governance.
- Data Enthusiasts who want to explore data handling, quality, and visualization techniques in AI.
- Tech Enthusiasts eager to learn about machine learning, generative AI, and robotics concepts.
- Ethics and Compliance Officers focused on understanding AI's ethical, legal, and regulatory implications.
- Professionals Transitioning to AI from other fields who need a solid introduction to AI and its business applicatio
Module 1: Introduction to Artificial and Human Intelligence
- Artificial Intelligence and Human Intelligence: A Comparative Overview
- The History of AI and Machine Learning
- Defining Machine Learning
- An Introduction to Data Science
- Hypothesis and Experimentation
- Beyond IQ and EQ: The Impact of Machine Learning
Module 2: Examples of AI - Benefits, Challenges, and Risks
- Key Steps and Requirements for Implementing Machine Learning
- Examples and Benefits of AI
- Challenges in Artificial Intelligence
- Identifying AI Risks
- Exploring Opportunities in AI
Module 3: Introduction to Machine Learning
- The AI Intelligent Agent
- Understanding Machine Learning
- Neural Networks Overview
- Data Preparation and Model Configuration
- Evaluating Algorithmic Models
- Applying and Validating Machine Learning Models for Real-World Use Cases
- Deploying Models for Practical Applications
- Model Diagnostics and Performance Optimization
- Optimizing Existing Statistical Models
Module 4: The Future of Artificial Intelligence - Human and Machine Integration
- Exploring the Future of AI: Collaboration Between Humans and Machines
- Understanding Key AI Terms
Skills You Will Learn
- Artificial intelligence fundamentals
- Machine learning, data science
- Neural networks
- Algorithm optimization, problem-solving
- Risk assessment in AI, and human-machine collaboration.
- Python, Scikit-learn, Pandas