This is an excellent course which not only helped me understand key definitions but has also excited to me to learn more in this field. Thank You to all the Instructors who made it easier for many like me.

I had a great time learning about AI, the different techniques used to train systems, and where AI is used in the real-world. This has undoubtedly sparked my curiosity in wanting to learn more.

A very useful course for a novice interested in the Artificial Intelligence. The course gives students the basic concepts about AI and also hands-on IBM labs to exercise AI techniques.

Amazing introductory course to get insights about different underlying algorithms and some possible pros and thought so cons associated with future of Advanced AI.

I enjoyed the class, and the information was presented in a clear manner that was easy to follow, understand, and retain.

Very good course to give a general perception of the basic foundation and concepts of AI in its current state. The learning material is good; however, since most of the material is video based, I have to criticize the audio mixing in all the videos. 1) There's always dramatic music in the background when people speak; which is super annoying. 2) The volume mixing of many videos is horrible, meaning that you as a learner have to adjust the volume on you device between speakers in the same video. Since some speak super quietly, and other blow you headphones. Course itself, 5/5 Material, 3/5

The course is a good overview of AI application and potential uses. Content is focused on the use of the Watson, the IBM AI platform. No programming is done. It's appropriate for non-coders.

please mute the music in presentations when people are speaking! good course

I am not able to get my certificate

Course doesn't bring to the point the interesting facts on AI. Examples and use cases stay at the surface (marketing level) whilst theoretic parts are way more difficult in relation. Test at the end can't be taken serious (testing the chatbot of a bank) and misuses students' time.

Watson VR was not available and in a week there was no solution, thus the course could not be completed unless you put a credit card. I think since the course is from IBM, it needs better communication between the owners of this course and IBM Cloud.

This course needs a lot of work. It offiered an HONORES certificate option with the Gold Tie if we complete the Honors portion of the course which was optional. Even though I completed the additional material I did not receive the Honors version of the certificate.

The honors material lacked any explaination on how to complete the excercise successfully and took my several times of completing the content to even completing it to understand what exactly they wanted. I had to employ my own techniques to create the IMAGES that they wanted me submit.

The course is not ready for commercial use.

A part of the content was quite good for fundamentals on AI. However, the second part of it was very much related to internal IBM policies and views which was less interesting or relevant. Another part of the content was not available - a handson assignment and the final assignment content. I would be looking for a different course to be able to truly get value and enjoy it.

Yeahh. Not pretty impressive. Just a couple of guys (and surely an oversmart kid boasting over his mere handful of knowledge) sharing their thoughts (read: Uttering random bullshit) over some random topics given by a reason-unknown overjoyed paaji. Information given is just 'opinions' and not proper facts,

This course is mostly like promoting what IBM is doing. I find this course is not useful.

lacking information

Great course up until the end. If you have issues creating an IBM Cloud Accout good luck on trying to finish the course. The only solution the staff has is to try other browsers or to use a different email. Oh and even if you get to create the account, the actual resources that you need to finish the Final project might not even be allocated to the account code that they give you. And their solution to that, send an email to support, ask for a new code and then TRY to make a new account even after all the trouble you went through to make the first one.

I don´t understand why this course has such high rating. It bring very top level info with low quality - most of the time you see people reading text from the screen, no visuals to understand difficult concepts. Big part of the course is proving that IBM tackles AI in the right way (AI ethics, etc.)

i have finished my course really early but after verify it resets my day i done. Then my instructor get misunderstanding and thought i finished late????

WHY I DIDNT GET ANY CERTIFICATE?

it should be more informative

Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, particularly computer systems. It is a broad field that involves several subfields such as machine learning, natural language processing, robotics, and computer vision. AI systems are designed to mimic human cognition, which includes the ability to reason, learn from experiences, and adapt to new situations. Here’s a review of the key concepts and areas of AI: 1. Types of AI Narrow AI (Weak AI): This type of AI is designed and trained to perform a specific task. Examples include voice assistants like Siri and Alexa, recommendation systems, and autonomous vehicles. Narrow AI operates within predefined parameters and doesn’t possess general cognitive abilities. General AI (Strong AI): This refers to a type of AI that can perform any intellectual task that a human can. It is capable of understanding and reasoning, adapting to a wide range of tasks. General AI is still a theoretical concept and hasn’t been realized yet. Superintelligent AI: This is a hypothetical AI that surpasses human intelligence across all fields, including creativity, problem-solving, and emotional intelligence. It could potentially change the dynamics of society and the economy. 2. Subfields of AI Machine Learning (ML): A subset of AI that involves algorithms that allow computers to learn from and make predictions or decisions based on data. There are three main types of machine learning: Supervised learning: The model is trained on labeled data. Unsupervised learning: The model works with unlabeled data to find patterns. Reinforcement learning: The model learns through rewards and punishments after taking actions. Natural Language Processing (NLP): This field focuses on the interaction between computers and human language. It enables machines to understand, interpret, and generate human language, such as with chatbots and virtual assistants. Computer Vision: This enables machines to interpret and make decisions based on visual data from the world, such as identifying objects or recognizing faces in images. Robotics: AI in robotics involves the design and control of robots that can perform tasks autonomously, often in environments where human intervention is limited or impossible. 3. Applications of AI Healthcare: AI is used in predictive analytics, medical imaging, drug discovery, and even robotic surgery. Finance: AI helps detect fraudulent transactions, automate trading, and assess risks in lending. Transportation: AI enables autonomous vehicles and smart traffic systems, enhancing safety and efficiency. Customer Service: Virtual assistants, chatbots, and personalized recommendations are AI applications that improve customer interactions. Manufacturing: AI optimizes production lines, predictive maintenance, and logistics. 4. Ethical Considerations The rise of AI raises important ethical concerns, including: Job displacement: Automation may replace certain jobs, leading to unemployment in some sectors. Bias and fairness: AI systems can inherit biases present in the data they are trained on, leading to unfair decisions. Privacy concerns: AI systems that collect and analyze personal data could infringe on privacy rights. Security risks: AI-powered cyberattacks and malicious uses of AI, such as deepfakes, pose significant risks. 5. Future of AI AI has the potential to revolutionize industries and improve quality of life, but it also brings challenges that need to be addressed. Research is ongoing in fields like explainable AI (to make AI decisions more transparent), as well as efforts to create stronger ethical guidelines and regulations for AI development. Conclusion Artificial Intelligence is a transformative technology with vast potential, and we are just scratching the surface of its possibilities. From automating routine tasks to solving complex problems, AI is reshaping how we live and work. However, with its rapid growth comes the responsibility to ensure that it is developed and used in ways that are beneficial, ethical, and secure.

Overview: The "Introduction to Artificial Intelligence (AI)" course provides a comprehensive foundation in AI concepts and applications. It covers key topics, including machine learning, natural language processing, computer vision, and ethical considerations in AI development. The course is designed for beginners, making it accessible to anyone interested in understanding the basics of AI. Content: The course content is well-structured, with clear explanations and real-world examples that illustrate complex concepts. Each module builds on the previous one, gradually introducing more advanced topics while ensuring that learners grasp the fundamentals. The inclusion of interactive exercises and quizzes enhances engagement and helps reinforce learning. Instructors: The instructors are knowledgeable and passionate about the subject matter. Their ability to simplify complex ideas and encourage questions creates an inviting learning environment. Additionally, they provide valuable insights into industry trends and future developments in AI. Practical Applications: One of the highlights of the course is its focus on practical applications. The course includes hands-on projects that allow students to apply what they've learned, which is invaluable for building confidence and competence in AI tools and techniques. Resources: The course offers a wealth of resources, including recommended readings, videos, and access to AI tools. The supplementary materials are well-curated and enhance the overall learning experience. Conclusion: Overall, the "Introduction to Artificial Intelligence (AI)" course is an excellent starting point for anyone looking to dive into the world of AI. It equips learners with the knowledge and skills needed to understand and engage with AI technologies. I highly recommend this course to anyone interested in exploring the exciting field of artificial intelligence!

🌟 Introduction to Artificial Intelligence (AI) 🤖 What is Artificial Intelligence? Artificial Intelligence (AI) refers to the simulation of human intelligence in machines. These systems are designed to think, learn, and make decisions similar to humans. 🧠 Types of AI Narrow AI (Weak AI): Performs a specific task (e.g., Siri, Google Translate). General AI (Strong AI): Has human-like intelligence and can perform any intellectual task a human can do (still theoretical). Super AI: Future concept where machines surpass human intelligence. 📚 Key Concepts in AI Machine Learning (ML): Algorithms that allow systems to learn from data and improve over time without being explicitly programmed. Deep Learning: A subset of ML using neural networks, often used in image and speech recognition. Natural Language Processing (NLP): Helps machines understand and communicate in human language. Computer Vision: Enables machines to interpret and understand visual information from the world. 🛠️ Applications of AI Healthcare: Diagnosing diseases, personalized treatment. Finance: Fraud detection, credit scoring. Retail: Chatbots, recommendation systems. Transportation: Self-driving cars, route optimization. Education: Smart tutoring, personalized learning. ⚖️ Ethical Considerations Bias & Fairness: Avoiding discrimination in AI decisions. Privacy: Protecting user data. Transparency: Understanding how AI makes decisions. Job Displacement: Balancing automation and employment. 🌍 Why AI Matters? AI is transforming every industry by: Increasing efficiency Automating tasks Enhancing decision-making Driving innovation

This was an exceptional overview of AI. From a pedagogical standpoint, I truly appreciated the linearity of the course pathway, in addition to the content being broken down into digestible videos. Further, the diverse set of presentations (interviews, white-boards, presentations, etc.) truly helped to maintain my focus. What shines, of course, is the content. And they made it about the content, not about IBM. I have taken some other courses not from IBM where much of the video's duration is taken up by company marketing copy. I marked, perhaps, two minutes total where IBM references one of their proprietary platforms/tech stack. The presenters who white-boarded were engaging, and they were deliberate and innovative with their note-taking. The visuals truly helped me process some of the more complex frameworks. As a side-note, I have a hunch that everyone is a HUGE fan of Martin Keen-- I sure am! I learned a great deal in this foundational course, and it's only increased my appetite for more. Through just this one course I see so much tremendous opportunity not just for myself, but so many who may be looking to take their skills and experience into new careers. Kudos IBM! I would recommend this course to anyone and everyone who needs a strong, comprehensive introduction!