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4Achievers Training Institute in Gurgaon offers a comprehensive Chat GPT Generative AI Training program that equips students with the skills needed to work with advanced AI models like ChatGPT. The course covers a wide range of topics, from understanding the fundamentals of Generative AI and Natural Language Processing (NLP) to practical applications such as building and deploying AI-powered chatbots, virtual assistants, and content generators. With expert instructors, live projects, and hands-on experience, students will gain a solid foundation in the rapidly growing field of AI and machine learning.
4Achievers focuses on offering real-world training with live projects, placement assistance, and access to world-class IT labs, ensuring that students are well-prepared to work on cutting-edge technologies and secure roles in AI development.
| Feature | Details |
|---|---|
| Course Duration | 2 to 3 months (Flexible batch options available) |
| Training Mode | Classroom & Online Training |
| Certification | Certification awarded on successful completion of the course |
| Project Work | Hands-on experience working with real-world ChatGPT projects |
| Batch Options | Weekdays, weekends, fast-track options available |
| Benefit | Description |
|---|---|
| Live Project Work | Students will work on AI-based projects, such as building chatbots and text-generating applications, to gain hands-on experience and build a portfolio. |
| Placement Assistance | 4Achievers ensures 100% job support, with career counseling, mock interviews, and resume building, to help students land jobs in top tech companies. |
| World-Class IT Lab | The institute is equipped with high-end machines, the latest software like TensorFlow, Python, and access to powerful cloud platforms, providing an ideal environment for AI development. |
| Personalized Learning | With small class sizes, personalized attention, and flexible learning schedules, students receive tailored instruction that meets their individual needs. |
| Project Type | Description |
|---|---|
| Chatbot Development | Build AI chatbots using ChatGPT to simulate human-like conversations for customer service, technical support, and personal assistants. |
| Content Generation | Use Generative AI to create articles, blogs, or social media content based on specific prompts or topics. |
| AI for Virtual Assistants | Develop AI-driven virtual assistants capable of handling multiple tasks, improving productivity, and user engagement. |
| Module | Topics Covered |
|---|---|
| Introduction to Generative AI | Understanding AI, NLP, and Generative AI principles, and how ChatGPT works. |
| Working with ChatGPT | Hands-on experience with the ChatGPT model and how to train and fine-tune it. |
| Natural Language Processing | Study of NLP techniques used in building AI that can understand and generate human-like text. |
| Building AI Models | Learn how to use Python, TensorFlow, and OpenAI API to build and deploy AI models. |
| Deploying AI Solutions | Learn to deploy AI models to real-world platforms for use in chatbots, virtual assistants, and content generators. |
| Reasons to Choose | Details |
|---|---|
| Hands-on Experience | With live projects and practical exercises, students get real-world exposure to AI tools and techniques. |
| Expert Trainers | Learn from trainers who are industry professionals with years of experience in Generative AI and ChatGPT development. |
| Advanced Infrastructure | Access to the latest AI tools, software, and technologies in the world-class IT lab ensures that students are working with cutting-edge resources. |
| Job Assistance | Placement support ensures students receive guidance, mock interviews, and job referrals, helping them secure roles in AI and tech companies. |
| Tool/Technology | Purpose |
|---|---|
| Python | For building and training AI models, including machine learning and NLP tasks. |
| TensorFlow | A key framework for building deep learning models, including generative models like ChatGPT. |
| OpenAI API | Access the ChatGPT model for creating AI-driven applications and services. |
| Natural Language Toolkit (NLTK) | A library for processing human language data and building NLP applications. |
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First touchpoint for customer Initial handling of all customer tickets Track to closure of customer tickets by assisting the responsible teams System software and AWS/Azure infrastructure L1/L2 support Newgen solution / application L1/L2 support Responsib
Experience: 0 to 4 years Qualification:B.SC, B.Tech/BE/MCA Skills in one or more of JavaScript,CSS, Web application framework viz. Sencha EXT JS, JQuery etc., Delphi,C,C++,or Java..net,testing Cloud Administrator-managing Windows based Servers
Developing and deploying new applications on the windows azure PAAS platform using C#, .net core . Participation in the creation and management of databases like SQL server and MySQL Understanding of data storage technology (RDBMS, NO SQL). Manage applica
Experience of Dev Ops technologies, architectures and processes for 3 yrs Cloud Infrastructures Solutions: AWS EC2 ECS, S3 Cloudfront, RDS, Spot Instances, VPC, IAM, Security Groups, ELB etc), GCP, CI/CD Jenkins Containerization: Docker, Kubernetes System
Must have good knowledge of Google Cloud (GCP), Good To Have- AWS and. Azure Cloud automation, with overall cloud computing experience. Good knowledge of Windows Server and IIS (Internet Information Services). Good knowledge of .NET applications (ASP.Net,
Good Knowledge in both Manual Testing and Automation Testing,Strong experience in writing test scenarios and test cases Strong knowledge on Selenium, Appium, Microsoft SQL and Jmeter Adept in functional testing and reporting defects
Design, execute and report software tests, Review business / software requirements and provide inputs. Prepare test cases, test scripts and test data., Execute tests (manual / automated). Report defects and assist in their understanding., Analyse test re
Good Knowledge in both Manual Testing and Automation Testing,Strong experience in writing test scenarios and test cases Strong knowledge on Selenium, Appium, Microsoft SQL and Jmeter Adept in functional testing and reporting defects
At 4Achievers Institute in Gurgaon, we integrate Agile methodologies into our Chat GPT Generative AI Training course to help students learn not only the technical aspects of Generative AI and ChatGPT, but also how to work efficiently in a team environment using Agile principles. This approach mimics real-world industry practices where teams work in short, iterative cycles, called sprints, to continuously improve AI models and deliver high-quality results.
By incorporating Agile activities such as sprint planning, daily stand-ups, sprint reviews, and retrospectives, students will develop the skills necessary to manage AI projects, collaborate effectively, and deliver working solutions in an agile, fast-paced environment.
Sprint Planning: In this phase, students break down their ChatGPT projects into manageable tasks. For example, one sprint could focus on fine-tuning the ChatGPT model, while another could focus on integrating it with real-world applications like chatbots or content generation tools.
Daily Stand-Ups: Every day, students gather for quick meetings to discuss their progress, share challenges, and make adjustments to their work. This helps keep everyone aligned and ensures smooth collaboration.
Sprint Review: At the end of each sprint, students demonstrate their work, whether it's an AI model trained on a new dataset or a chatbot that is now capable of more human-like conversations. This allows the team and instructor to assess the quality of the work and identify areas for improvement.
Sprint Retrospective: After the sprint review, students reflect on what went well, what challenges they faced, and how they can improve in the next sprint. This self-reflection helps students continually improve their work habits and technical skills.
| Agile Activity | Benefits for Students |
|---|---|
| Sprint Planning | Students learn how to break complex tasks into manageable chunks and prioritize work efficiently. |
| Daily Stand-Ups | Encourages continuous communication, helping students identify and resolve issues quickly. |
| Sprint Review | Provides an opportunity for students to showcase their work, get feedback, and learn how to make improvements. |
| Sprint Retrospective | Allows students to reflect on their processes, identify improvement areas, and develop better work habits. |
| Agile Activity | Impact on Learning |
|---|---|
| Sprint Planning | Students learn project management skills and how to break down AI tasks into actionable steps, ensuring that the learning process is organized and effective. |
| Daily Stand-Ups | Fosters collaboration, making students comfortable with sharing their ideas, challenges, and solutions. This teamwork is essential for building large AI projects like ChatGPT. |
| Sprint Review | Provides practical feedback on their progress with ChatGPT, ensuring that students receive constructive criticism to refine their models and solutions. |
| Sprint Retrospective | Helps students build a growth mindset, continuously improving their approach to AI projects and learning how to overcome obstacles in AI development. |
| Agile Phase | Activities in Chat GPT Generative AI Project |
|---|---|
| Sprint Planning | - Define user stories (e.g., "As a data scientist, I want to fine-tune a ChatGPT model for customer support") - Set clear goals for each sprint (e.g., improving chatbot responses) |
| Daily Stand-Ups | - Discuss the progress of model training - Resolve technical issues with dataset preprocessing or fine-tuning |
| Sprint Review | - Present working ChatGPT models or deployed chatbots - Demonstrate improvements in AI-generated content or conversation capabilities |
| Sprint Retrospective | - Reflect on the challenges faced (e.g., model performance issues) - Identify ways to improve the development process (e.g., more efficient dataset cleaning techniques) |
| Agile Concept | Description |
|---|---|
| User Stories | In Agile, tasks are written as user stories, which helps students focus on the end user's needs when building ChatGPT models. For example, "As a user, I want the AI to generate coherent product descriptions" focuses on delivering value. |
| Backlog Grooming | Students learn to manage and prioritize tasks in the backlog, ensuring that the most important features, like enhancing ChatGPT's ability to understand context, are handled first. |
| Continuous Integration | Students practice integrating changes into their ChatGPT models regularly, ensuring that progress is continuous and any issues are caught early. |
| Sprint Goals | Clear goals are set for each sprint, which could involve tasks like improving the AI's ability to generate more natural responses or testing the chatbot's functionality with real users. |
Using Agile methodologies in Chat GPT Generative AI Training allows students to:
| Benefit | Description |
|---|---|
| Collaboration | Students work in teams, improving their ability to collaborate on complex AI projects. |
| Adaptability | Agile's iterative approach allows students to adapt to changing requirements and challenges, which is essential in AI development. |
| Faster Delivery | Through Agile sprints, students complete parts of their ChatGPT projects faster, leading to quicker feedback and iteration cycles. |
4Achievers offers the step-by-step guide to get your dream job after completing Course.
