Top 5 Popular Online Courses to Master Generative AI in 2024

Generative AI is one of the rapidly growing fields in Artificial Intelligence. Generative AI mentions the potential of Artificial Intelligence (AI) systems not just to learn data but to create realistic data such as Images, Text, Audio, Video, music, and many others. Generative AI is enabled with a broader range of applications from magnifying entertainment and creativity to solving real-world problems along with cutting-edge scientific research.

However, what is the best way to acquire and become proficient in this advanced technology? What are the necessary skills and tools to excel in generative AI by 2024? This blog post aims to delve into the fundamental skillsets required for generative AI and offer valuable resources and advice to assist you in getting started.

What is Generative AI?

Generative AI is a branch of Artificial Intelligence that provides attention not just to developing new realistic data but also to learning the new data or content that duplicates the distribution and attributes of existing data. Let us understand generative AI with an example, It can develop realistic images of animals, landscapes, humans, or objects that don't even exist. Generative AI can easily generate stories, articles, summaries, or captions in natural language. The power of Artificial intelligence-enabled Generative AI can effortlessly generate music, games, videos, or art using several inputs and styles.

Generative AI is enabled with a broader range of algorithms and techniques, including generative adversarial networks (GANs), variational autoencoders (VAEs), autoregressive models, diffusion models, and reinforcement learning. These algorithms and techniques enable the AI system to generate unique and authentic outputs after getting insights from a broader range of data.

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Benefits and applications of Generative AI

• Magnifying creativity and entertainment: Generative AI has the potential to assist artists, designers, musicians, and gamers in producing fresh and unique content, including images, logos, songs, characters, and worlds. Moreover, Generative AI can offer customized and engaging experiences, such as chatbots, virtual assistants, and interactive storytelling.
• Real-world problem-solving and advancing scientific research: Researchers and practitioners can take benefit from generative AI to synthesize and analyze various types of data, including medical images, drug molecules, protein structures, and climate models. Additionally, Generative AI can assist in generating realistic simulations, scenarios, and experiments, such as those related to traffic, weather, and social behavior.
• Improving Data Quality and Privacy: Generative AI can efficiently help in improving the quality of data, including removing noise, filling out missing places, and strengthening resolution. Generative AI is capable of protecting the privacy of data, like hiding confidential information, preventing loopholes that may cause data leakage, and generating synthetic data.

Top Generative AI courses in 2024

1. Data Science with Generative AI: The Generative AI-enabled Data Science course will help students learn advanced concepts and unveil the capability of generative AI. Candidates who are seeking to step into the ever-evolving domain of Data Science or working professionals who are seeking career advancement in this domain will learn to incorporate generative AI advanced tools including Python, ChatGPT, NumPy, Flask, DaLLE, Scikit Learn, Jupyter, Lang Chain, PyTorch, and more. Industry professionals will teach candidates the meticulously tailored industry-specific curriculum of the course that perfectly blends theoretical and practical knowledge.

2. Generative AI with TensorFlow: The generative AI course on the Coursera platform is a 16-hour long duration course. The course holds recognition from major tech organizations such as Microsoft, Google, etc. On completion of the course, candidates will get a certificate that will help them in lending in a Generative AI job. What makes this course from Coursera apart from others is the course availability in 19 different languages. Candidates enrolling in this course will be able to develop skills in Fundamentals of Generative AI, machine learning, NumPy, AI Models, Python, ChatGPT, flask, PyTorch, etc. Below listed are some modules that will be covered during the course:

• Style Transfer
• AutoEncoders
• Variational AutoEncoder
• GANs

3. Generative Adversarial Networks by Udacity: Generative AI offered by Udacity provides candidates the opportunity to gain knowledge in deep complex Generative AI networks, enabling them to generate realistic images, videos, and more. The Generative AI Adversarial Networks by Udacity spans 4 weeks (1 month) and provides candidates with access to real-world projects and completion certificates.

During the course, candidates will gain insight into core subjects of Generative Adversarial Networks that are mentioned below:

• Introduction to Generative Adversarial Networks
• Generative Adversarial Networks
• Training a Deep Convolutional GANs
• Image-to-Image Translation
• Modern GANs
• Face Generation

4. Stanford University’s Deep Generative AI Models: The AI-enabled Deep Generative AI-model course at Stanford University is provided by well-versed experts of the Stanford University. This course will cover every important aspect of machine learning and generative AI. students will learn about concepts like Deep Learning, Machine Learning, CNN, etc. Here are some subjects mentioned that are being taught during this course:

• Introduction of Deep Learning 
• Convolutional Neural Networks (CNNs)
• Recurrent Neural Networks (RNNs)
• Generative AI Deep Learning Models
• Autoregressive models
• Normalising Flow Models
• Generative Adversarial Networks
• Evaluation of Generative AI models

5. Introduction to Learning Generative AI by Google: Google Cloud has released several courses that are based on Artificial Intelligence (AI) and Machine Learning (ML). students will gain a principal overview of generative AI concepts. However, the course is divided into 5 different packages:

• Introduction to Generative AI
• Introduction to Large Langauge Models
• Introduction to Responsible AI
• Generative AI Fundamentals
• Responsible AI: Applying AI Principles with Google Cloud

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