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· Introduction to GEN AI
· Overview of LangChain
· Introduction to OpenAI
· Understanding LLAMA
· Introduction to ChatGPT
· Setting Up Development Environment for LangChain
· Configuring Development Environment for OpenAI
· Environment Setup for LLAMA
· Setting Up Development Environment for ChatGPT
· Model Module
· Prompt Module
· Chains Module
· Agent Module
· Memory Module
· Retrieval Data Connection Module
· Question & Answer Module
· Conversational Module
· Marketing Module
· CSV data Analysis Module
· Text to Query Module
· Code Review Module
· Capstone Project-Session 1
o Aligning with the course content, the capstone project serves as a culmination of your learning experience.
o You'll apply your knowledge and skills acquired throughout the course to solve a real-world problem or tackle a challenging task.
o The project will be divided into multiple sessions, each focusing on specific aspects such as data preparation, model development, evaluation, and deployment.
o Sessions will include interactive discussions, hands-on exercises, and guidance from instructors to ensure successful project completion.
o Projects will cover a range of domains including but not limited to image classification, natural language processing, and predictive analytics.
o Through the capstone project, you'll demonstrate your proficiency in Deep Learning concepts and methodologies, and showcase your ability to deliver impactful solutions.
o 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
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.
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.
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.
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:
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.
· 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.
Total Duration is 48 hours
Salary Estimates as on October 8th, 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.
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.
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.
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.
While we do work in R and Python during the training, knowledge of any programming language will work- as we teach the principles from a “software agnostic” point of view, the principles transfer across programming languages. We teach how to interpret data, and then how to apply machine learning to take that to the next level.
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.
Yes, you will receive grades for your work during the course.
Once you successfully complete the Data Science with Python, Machine Learning & AI Professional course, Global IT will provide you with an industry-recognized course completion certificate which will have a lifelong validity.
Yes, we provide both course materials and practice tests as part of our course curriculum to help you prepare for the actual certification exam.
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.
You can give us a CALL at Toll Free: (866)-GO-GIT-GO OR email at info@global-itech.com
In our Job Assistance program, we will be helping you land in your dream job by sharing your resume to potential recruiters and assisting you with resume building, preparing you for interview questions. GIT’s training should not be regarded either as a job placement service or as a guarantee for employment as the entire employment process will take part between the learner and the recruiter companies directly and the final selection is always dependent on the recruiter.
All the instructors at Global IT are practitioners from the Industry with minimum 5-10 years of relevant IT experience. They are subject matter experts and are passionate for providing an awesome learning experience to the participants.
· Introduction to GEN AI
· Overview of LangChain
· Introduction to OpenAI
· Understanding LLAMA
· Introduction to ChatGPT
· Setting Up Development Environment for LangChain
· Configuring Development Environment for OpenAI
· Environment Setup for LLAMA
· Setting Up Development Environment for ChatGPT
· Model Module
· Prompt Module
· Chains Module
· Agent Module
· Memory Module
· Retrieval Data Connection Module
· Question & Answer Module
· Conversational Module
· Marketing Module
· CSV data Analysis Module
· Text to Query Module
· Code Review Module
· Capstone Project-Session 1
o Aligning with the course content, the capstone project serves as a culmination of your learning experience.
o You'll apply your knowledge and skills acquired throughout the course to solve a real-world problem or tackle a challenging task.
o The project will be divided into multiple sessions, each focusing on specific aspects such as data preparation, model development, evaluation, and deployment.
o Sessions will include interactive discussions, hands-on exercises, and guidance from instructors to ensure successful project completion.
o Projects will cover a range of domains including but not limited to image classification, natural language processing, and predictive analytics.
o Through the capstone project, you'll demonstrate your proficiency in Deep Learning concepts and methodologies, and showcase your ability to deliver impactful solutions.
o 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
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.
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.
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.
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:
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.
· 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.
Total Duration is 48 hours
Salary Estimates as on October 8th, 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.
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.
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.
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.
While we do work in R and Python during the training, knowledge of any programming language will work- as we teach the principles from a “software agnostic” point of view, the principles transfer across programming languages. We teach how to interpret data, and then how to apply machine learning to take that to the next level.
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.
Yes, you will receive grades for your work during the course.
Once you successfully complete the Data Science with Python, Machine Learning & AI Professional course, Global IT will provide you with an industry-recognized course completion certificate which will have a lifelong validity.
Yes, we provide both course materials and practice tests as part of our course curriculum to help you prepare for the actual certification exam.
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.
You can give us a CALL at Toll Free: (866)-GO-GIT-GO OR email at info@global-itech.com
In our Job Assistance program, we will be helping you land in your dream job by sharing your resume to potential recruiters and assisting you with resume building, preparing you for interview questions. GIT’s training should not be regarded either as a job placement service or as a guarantee for employment as the entire employment process will take part between the learner and the recruiter companies directly and the final selection is always dependent on the recruiter.
All the instructors at Global IT are practitioners from the Industry with minimum 5-10 years of relevant IT experience. They are subject matter experts and are passionate for providing an awesome learning experience to the participants.
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· Introduction to GEN AI
· Overview of LangChain
· Introduction to OpenAI
· Understanding LLAMA
· Introduction to ChatGPT
· Setting Up Development Environment for LangChain
· Configuring Development Environment for OpenAI
· Environment Setup for LLAMA
· Setting Up Development Environment for ChatGPT
· Model Module
· Prompt Module
· Chains Module
· Agent Module
· Memory Module
· Retrieval Data Connection Module
· Question & Answer Module
· Conversational Module
· Marketing Module
· CSV data Analysis Module
· Text to Query Module
· Code Review Module
· Capstone Project-Session 1
o Aligning with the course content, the capstone project serves as a culmination of your learning experience.
o You'll apply your knowledge and skills acquired throughout the course to solve a real-world problem or tackle a challenging task.
o The project will be divided into multiple sessions, each focusing on specific aspects such as data preparation, model development, evaluation, and deployment.
o Sessions will include interactive discussions, hands-on exercises, and guidance from instructors to ensure successful project completion.
o Projects will cover a range of domains including but not limited to image classification, natural language processing, and predictive analytics.
o Through the capstone project, you'll demonstrate your proficiency in Deep Learning concepts and methodologies, and showcase your ability to deliver impactful solutions.
o 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
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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.
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.
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.
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:
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.
· 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.
Total Duration is 48 hours
Salary Estimates as on October 8th, 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.
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.
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.
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.
While we do work in R and Python during the training, knowledge of any programming language will work- as we teach the principles from a “software agnostic” point of view, the principles transfer across programming languages. We teach how to interpret data, and then how to apply machine learning to take that to the next level.
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.
Yes, you will receive grades for your work during the course.
Once you successfully complete the Data Science with Python, Machine Learning & AI Professional course, Global IT will provide you with an industry-recognized course completion certificate which will have a lifelong validity.
Yes, we provide both course materials and practice tests as part of our course curriculum to help you prepare for the actual certification exam.
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.
You can give us a CALL at Toll Free: (866)-GO-GIT-GO OR email at info@global-itech.com
In our Job Assistance program, we will be helping you land in your dream job by sharing your resume to potential recruiters and assisting you with resume building, preparing you for interview questions. GIT’s training should not be regarded either as a job placement service or as a guarantee for employment as the entire employment process will take part between the learner and the recruiter companies directly and the final selection is always dependent on the recruiter.
All the instructors at Global IT are practitioners from the Industry with minimum 5-10 years of relevant IT experience. They are subject matter experts and are passionate for providing an awesome learning experience to the participants.
Expanded baseline security topics essential for IT support, including physical vs. logical security concepts, malware, and more.
A revised approach to operational procedures, covering basic disaster prevention, recovery, and scripting basics.
A stronger focus on networking and device connectivity
