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Innovate the Future with Intelligent Creation
The Generative AI Development Program empowers you to master the most revolutionary technology shaping industries today. Learn how to build intelligent systems capable of generating text, images, code, and insights using cutting-edge AI frameworks like OpenAI, TensorFlow, PyTorch, and LangChain.
This program takes you from foundational AI and deep learning concepts to advanced prompt engineering, model fine-tuning, and application deployment, preparing you for global opportunities in AI research, automation, and intelligent software development.
8th October
07:00 AM TO 08:00 AM
80-100 Days
Training
At JVSIT & TGS Training Institute, our Generative AI Development course is designed to equip learners with end-to-end expertise in building and deploying generative models. From understanding neural network architectures to building real-world AI applications, you’ll gain the hands-on skills required to excel in one of the fastest-growing tech domains.
Day 1
Types of applications
Roles in software industry
Responsibilities of each role
Introduction to What WG
Day 2
Software development life cycles
Types of SDLC
Day 3
Water Fall Model
V Model
Circler Model
Day 4
Agile Model
Domain choosing
Project choosing
Modules and functionalities finding
Day – 5
Introduction to UI-UX
Introducing FIGMA tool
Day – 6
Optimal design principles of database, business logic
Time and Space complexity
Day 7
GitHub with sample HTML page
Creating Repos
Creating LinkedIn account
Day 8
Difference between platform and domain
Requirement gathering for 2 real time scenarios using Agile
Day 9
Deployment methods on hostings
Knowledge about servers and load balancers
Day 10
Power of AI and prompting (webinar)
Using Copilot tool
Using ChatGPT
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Form tags and Attributes
MultiMedia tags
Assignment – Naasongs.
Assignment – Sample login, register, forgot password pages
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Hibernate and Spring
Day – 1
1.Introduction to Spring Boot
2.Setting Up Spring Boot and Creating a Basic Program
If you need the sample Spring Boot application code as text:
java
}
Day – 2
text
// Sample application.properties
spring.datasource.url=jdbc:h2:mem:testdb
spring.jpa.hibernate.ddl-auto=update
Day – 3
text
// Sample Actuator Configuration
management.endpoints.web.exposure.include=health
Day – 4
java
// Sample JPA Entity
@Entity
public class User {
@Id
@GeneratedValue(strategy = GenerationType.IDENTITY)
private Long id;
private String name;
// getters and setters
}
Day – 5
java
// Sample Security Configuration
@Configuration
@EnableWebSecurity
public class SecurityConfig extends WebSecurityConfigurerAdapter {
@Override
protected void configure(HttpSecurity http) throws Exception {
http
.csrf().disable()
.authorizeRequests()
.antMatchers(“/public/**”).permitAll()
.anyRequest().authenticated();
}
}
Day – 6
java
// Sample REST Controller
@RestController
@RequestMapping(“/api/users”)
public class UserController {
@GetMapping
public List getAllUsers() {
// return list of users
}
@PostMapping
public User createUser(@RequestBody User user) {
// create and return user
}
}
Day – 7
text
# Sample Dockerfile
FROM openjdk:11-jre-slim
COPY target/demo-0.0.1-SNAPSHOT.jar app.jar
ENTRYPOINT [“java”, “-jar”, “/app.jar”]
Day – 8
java
// Sample Eureka Server Configuration
@SpringBootApplication
@EnableEurekaServer
public class EurekaServerApplication {
public static void main(String[] args) {
Day – 9
java
// Sample Microservice Configuration
@SpringBootApplication
@EnableDiscoveryClient
public class MicroserviceApplication {
public static void main(String[] args) {
SpringApplication.run(MicroserviceApplication.class, args);
}
}
SpringApplication.run(EurekaServerApplication.class, args);
}
}
Day – 10
java
// Sample Asynchronous Method
@Service
public class MyService {
@Async
public CompletableFuture AsyncMethod() {
return CompletableFuture.completedFuture(“Async Result”);
}
}
Day – 11
text
# Sample Kubernetes Deployment YAML
apiVersion: apps/v1
kind: Deployment
metadata:
name: spring-boot-app
spec:
replicas: 2
selector:
matchLabels:
app: spring-boot-app
template:
metadata:
labels:
app: spring-boot-app
spec:
containers:
– name: spring-boot-app
image: spring-boot-app:latest
ports:
– containerPort: 8080
It’s a professional training program that teaches you how to design, train, and deploy generative AI models using frameworks like OpenAI, TensorFlow, PyTorch, and LangChain.
Students, developers, data scientists, and AI enthusiasts who want to specialize in creating intelligent, generative systems for text, image, or code.
Basic understanding of Python and machine learning is helpful but not mandatory. Beginners can easily follow with the structured learning path.
You’ll learn neural networks, deep learning, transformers, prompt engineering, LLM fine-tuning, and real-world AI application deployment.
You’ll work hands-on with OpenAI API, Hugging Face Transformers, PyTorch, TensorFlow, LangChain, and other leading AI development tools.
Empowering careers with tech and hands-on learning. 15,000+ trained, 10,000+ placed, 20+ global partners.
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