Generative AI course

In this course, you will learn the fundamentals of generative artificial intelligence (AI), including concepts such as Generative Adversarial Networks (GANs) and language generation models. You’ll gain practical skills in setting up development environments and working with tools like LangChain, OpenAI, and LLAMA. Through hands-on modules and projects, you’ll explore various applications of generative AI, including question answering, conversational agents, marketing analytics, data analysis, and text-to-query systems. Additionally, you’ll collaborate on a capstone project, applying your knowledge to solve real-world problems and showcase your proficiency in deep learning concepts and methodologies. Overall, this course provides a comprehensive understanding of generative AI and its potential across different industries and domains.

The Generative AI course offers several benefits:

1. In-demand Skills: Acquire sought-after skills in generative artificial intelligence (AI), including GANs and language generation models, enhancing your career prospects in AI research, development, and application.
2. Practical Experience: Gain hands-on experience setting up development environments and working with tools like LangChain, OpenAI, and LLAMA, preparing you for real-world projects and challenges.
3. Diverse Applications: Explore diverse applications of generative AI, including question answering, conversational agents, marketing analytics, data analysis, and text-to-query systems, enabling you to apply your skills across different industries and domains.
4. Capstone Project: Collaborate on a capstone project, solving real-world problems and showcasing your proficiency in deep learning concepts and methodologies, which can serve as a portfolio piece for future career opportunities.
5. Networking Opportunities: Connect with peers, instructors, and industry professionals through discussions, forums, and networking events, expanding your professional network and potentially opening doors to new career opportunities.
6. Career Advancement: Enhance your career prospects by staying updated on the latest advancements in generative AI and positioning yourself as a skilled professional in this rapidly evolving field.
7. Creative Exploration: Explore the intersection of AI and creativity, unlocking new possibilities for creative expression and innovation in areas such as art, design, writing, and music.

Overall, the Generative AI course equips you with valuable skills, practical experience, and networking opportunities to succeed in the dynamic and rapidly growing field of artificial intelligence.

Intro to GEN AI, LangChain, OPENAI, LLAMA, ChatGPT

• Introduction to GEN AI
• Overview of LangChain
• Introduction to OpenAI
• Understanding LLAMA
• Introduction to ChatGPT

Development Environment Setup

• Setting Up Development Environment for LangChain
• Configuring Development Environment for OpenAI
• Environment Setup for LLAMA
• Setting Up Development Environment for ChatGPT

LangChain Modules:

• Model Module
• Prompt Module
• Chains Module
• Agent Module

Continuation of LangChain Modules:

• Memory Module
• Retrieval Data Connection Module

Project:

• Question & Answer Module
• Conversational Module
• Marketing Module
• CSV data Analysis Module
• Text to Query Module
• Code Review Module
• Capstone Project-Session 1
  • Aligning with the course content, the capstone project serves as a culmination of your learning experience.
  • You’ll apply your knowledge and skills acquired throughout the course to solve a real-world problem or tackle a challenging task.
  • The project will be divided into multiple sessions, each focusing on specific aspects such as data preparation, model development, evaluation, and deployment.
  • Sessions will include interactive discussions, hands-on exercises, and guidance from instructors to ensure successful project completion.
  • Projects will cover a range of domains including but not limited to image classification, natural language processing, and predictive analytics.
  • Through the capstone project, you’ll demonstrate your proficiency in Deep Learning concepts and methodologies, and showcase your ability to deliver impactful solutions.
  • The project will culminate in a final presentation or report where you’ll present your findings, methodologies, and outcomes to peers and instructors for feedback and evaluation.
• Capstone Project-Session 2 & Q & A session

1. What is Generative AI course?

The Generative AI course explores the fascinating field of artificial intelligence focused on generating new content, such as images, text, and music, using machine learning algorithms. Participants will learn about various generative models and techniques, including generative adversarial networks (GANs) and autoencoders, and how to implement them using Python programming. This course provides hands-on experience in creating AI systems that can autonomously generate creative and innovative outputs, making it an exciting and valuable skill set in the rapidly evolving field of artificial intelligence.

2. Why Generative AI Course?

The Generative AI course offers a unique opportunity to delve into the cutting-edge field of artificial intelligence focused on creative content generation. With the increasing demand for AI-driven innovations in various industries, mastering generative AI techniques opens doors to exciting career opportunities in fields such as art, design, entertainment, and more. This course equips participants with the skills and knowledge needed to create AI systems capable of autonomously generating diverse and innovative content, making it a valuable asset for anyone looking to stay ahead in the rapidly evolving world of artificial intelligence.

3. Is this course suitable for beginners in AI and machine learning?

The course is designed to accommodate learners at various skill levels, including beginners. However, individuals with some prior knowledge or experience in AI, machine learning, or programming may find it easier to grasp the concepts covered in the course.

4. What is OpenAI?

OpenAI is an artificial intelligence research laboratory and technology company. It is known for developing advanced AI models and algorithms, including GPT (Generative Pre-trained Transformer) models like ChatGPT.

5. What is ChatGPT?

ChatGPT is a variant of OpenAI’s GPT model specifically designed for generating human-like text responses in conversational settings. It can be used for building chatbots, virtual assistants, and other interactive applications.

6. Who should go for this Training?

Individuals looking for a career in programming or are currently working as developers, programmers, Freelance Artists, designers or web developers should attend this course. The course covers basic data science along with all advance features that an individual will perform as a data science professional. So, this course will help IT Developer, Project Manager and Analytics Professional to grow in their analytics journey.

7. What are Job Prospects of this course?

The job prospects for graduates of the Generative AI course are promising, with opportunities available in various industries that require creative content generation and innovative problem-solving. Some potential job roles include:

1. AI Researcher: Conducting research and development in the field of generative AI to advance the state-of-the-art in creative content generation.
2. Data Scientist: Using generative AI techniques to analyze and generate insights from large datasets, particularly in fields such as marketing, finance, and healthcare.
3. Software Engineer: Developing and implementing generative AI algorithms and systems for applications such as image and video synthesis, natural language generation, and music composition.
4. Creative Technologist: Collaborating with artists, designers, and content creators to integrate generative AI techniques into interactive and immersive experiences.
5. Product Developer: Leveraging generative AI to develop innovative products and services, such as personalized recommendations, virtual assistants, and content creation tools.
6. AI Consultant: Providing expertise and guidance to businesses on how to leverage generative AI technologies to enhance creativity, productivity, and competitiveness.
7. Freelance Artist/Designer: Using generative AI tools and techniques to create unique and original artwork, designs, and multimedia content for clients and projects.

8. What background knowledge is necessary?

Not required as such. Anyone with an aptitude for learning programming and has interest for doing analysis on data can be a good fit for this course. The course will use python programming language for doing data analysis so python programming language will be taught as part of this course.

9. What will I learn in this course?

• Generative Models: Understand techniques like GANs and VAEs.
• Python Programming: Master Python libraries like TensorFlow and PyTorch.
• Data Handling: Learn data preprocessing and manipulation.
• Neural Networks: Explore CNNs and RNNs for tasks like image and text generation.
• Training and Optimization: Optimize models for better performance.
• Evaluation: Assess model outputs for quality and diversity.
• Creative Applications: Apply generative AI in image, text, and music generation.
• Ethical Considerations: Address issues like bias and privacy in AI.
• Project Management: Manage end-to-end AI projects effectively.

10. What is the duration of this Course?

Total Duration is 48 hours

11. What are Job prospects for this Gen AI course and how much can I earn?

The job prospects for graduates of a Generative AI course are promising due to high demand across various industries, opportunities for innovation, and competitive salaries in specialized roles.

AI Developer/Engineer:

Entry-Level: $70,000 – $120,000

Mid-Level: $100,000 – $150,000

Senior-Level: $130,000 – $200,000+

Machine Learning Engineer:

Entry-Level: $80,000 – $130,000

Mid-Level: $110,000 – $160,000

Senior-Level: $140,000 – $220,000+

AI Product Manager:

Entry-Level: $80,000 – $120,000

Mid-Level: $110,000 – $150,000

Senior-Level: $140,000 – $200,000+

Digital Marketing Analyst:

Entry-Level: $45,000 – $65,000

Mid-Level: $60,000 – $90,000

Senior-Level: $80,000 – $120,000+

Digital Transformation Consultant:

Entry-Level: $60,000 – $90,000

Mid-Level: $80,000 – $120,000

Senior-Level: $100,000 – $150,000+

12. how much does a Data Scientist earn?

Salary Estimates as on October 8^th, 2020 in for a Data Scientist in USA are

Zip Recruiter – 76K-160K per Year

Glass Door – 83K-150K per Year

PaySclae USA – 67K-130K per Year

The average salary for a Data Scientist in Detroit, Michigan is $87815 as per PaySclae USA.

13. What are the prerequisites for this course?

There is no pre-requisite as such. Anyone with an aptitude for learning programming and interest for doing analysis on data can be the good fit for this course. The course will use python programming language for doing data analysis so python programming language will be taught as part of this course.An understanding of programming languageis an advantage.

14. What skills do I learn in this course – Generative AI Course?

In the Generative AI course, you will learn a variety of skills essential for creating AI systems capable of generating creative content. Some of the key skills you will acquire include:

• Understanding Generative Models: Learn the principles and techniques behind generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs).
• Python Programming: Gain proficiency in Python programming language, including libraries such as TensorFlow and PyTorch, for implementing generative AI algorithms.
• Data Manipulation and Preprocessing: Learn how to preprocess and manipulate datasets to prepare them for training generative AI models.
• Neural Network Architectures: Understand different neural network architectures used in generative AI, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
• Training and Optimization: Learn techniques for training and optimizing generative AI models to generate high-quality and diverse outputs.
• Evaluation and Validation: Understand methods for evaluating and validating the performance of generative AI models, including qualitative and quantitative metrics.
• Creative Content Generation: Explore various applications of generative AI in generating images, text, music, and other forms of creative content.
• Ethical and Social Implications: Consider the ethical and social implications of generative AI technologies, including issues related to bias, privacy, and authenticity.
• Project Management: Gain experience in managing generative AI projects, from problem formulation and data collection to model development and deployment.
• Collaboration and Communication: Develop skills in collaborating with multidisciplinary teams and effectively communicating complex concepts and ideas related to generative AI.

15. What is the Capstone Project?

The Capstone Project is a comprehensive project where you apply your knowledge and skills acquired throughout the course to solve a real-world problem or tackle a challenging task. It consists of multiple sessions focusing on different aspects of project development and culminates in a final presentation or report.

16. How do I become a Data Scientist?

This course is designed to give you an insight into Industry driven Data Science tools and methodologies, which is enough to prepare you to excel in your next role as a Data Scientist. The program will train you on R and Python, Machine Learning techniques, data preprocessing, regression, clustering, data analytics, statistics for model building and evaluation, the theory and methods of advanced analytics and statistical modeling, the technology and tools that can be used for advanced analytics, operationalizing an analytics project, and data visualization techniques.

17. What software/technology stacks do you use?

In the Generative AI course package, various software and technology stacks are utilized to teach and implement concepts related to generative AI, deep learning, and natural language processing. Some of the key software and technology stacks used in the course may include:

• Python:
• Jupyter Notebooks:
• TensorFlow:
• PyTorch:
• OpenAI API:
• GitHub:
• Terminal/Command Line Interface (CLI):
• Virtual Environments (e.g., conda, virtualenv):
• Development Tools:
• Other Tools and Libraries:

18. How much statistics will I need to know?

We work hard to ensure that no prior statistics knowledge is required. We will teach you all the basics you need to know before and during the bootcamps. We cover correlations, hypothesis testing, and Linear Regression in the Course, all at a level appropriate for someone with no/little statistics experience.

19. Do we receive grades?

Yes, you will receive grades for your work during the course.

20. Who provides the certification and how long does its valid?

Once you successfully complete the Data Science with Python, Machine Learning, Deep Learning&Gen AI Professional course, Global IT will provide you with an industry-recognized course completion certificate which will have a lifelong validity.

21. Do you provide any material or practice tests during the course?

Yes, we provide both course materials and practice tests as part of our course curriculumto help you prepare for the actual certification exam.

22. What is the difference between a Data Scientist, Data Analyst, and Data Engineer?

We’ve certainly seen variation in regards to what employers have in mind when they use these terms, so please consider the answers below as general guidelines.

A Data Analyst is someone who creates and communicates insights from data to measure outcomes, make predictions, and guide business decisions. Often, there is a lighter coding burden placed upon someone with the title Data Analyst, though they may be expected to know certain languages or packages in R or python.

A Data Engineer is the designer, builder, and manager of the information or “big data” infrastructure. Each develops the architecture that helps analyze and process data in the way the organization needs it – and they make sure those systems are performing smoothly.

The term Data Scientist is used the most broadly. A job posting for a Data Scientist might describe a role identical to others calling for “data analyst,” though there is usually more diverse coding skills needed for a data scientist job. For the most part, data scientists are asked to participate in the entire cycle of problems and solutions. They help identify opportunities for companies to use data, while also finding, collecting, and integrating relevant data sources, performing analyses of varying degrees of complexity, writing code and creating tools that teams and businesses can use over time, and telling the story of what they’ve done to company stakeholders.