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Empower Data. Drive Intelligence. Transform the Future.
The Data Science with AI & Machine Learning Program at JVSIT & TGS Training Institute is designed to help you master the art of turning raw data into actionable intelligence. Learn how to analyze, visualize, and model data using powerful tools and algorithms that power today’s AI-driven world.
This program takes you from data fundamentals to advanced AI and ML concepts, including data preprocessing, predictive modeling, neural networks, and automation, preparing you for global opportunities in data analytics, AI engineering, and machine learning development.
8th October
07:00 AM TO 08:00 AM
80-100 Days
Training
At JVSIT & TGS Training Institute, our Data Science with AIML program blends data analytics, statistical modeling, and AI-driven insights into a single, job-oriented learning path. You’ll gain hands-on experience working with real datasets, applying algorithms, and building machine learning models that solve real-world business problems.
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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Day – 6
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 collect, process, analyze, and model data using AI and machine learning techniques.
Students, developers, analysts, and professionals aspiring to start or advance their career in Data Science, AI, or Machine Learning.
Basic knowledge of Python and mathematics (statistics, algebra) is helpful, but beginners can easily learn with guided instruction.
You’ll learn Python for data science, machine learning algorithms, data visualization, deep learning, NLP, and model deployment.
You’ll work hands-on with Python, TensorFlow, Scikit-learn, Pandas, NumPy, Power BI, Matplotlib, and Jupyter Notebooks for data analytics and AI development.
Empowering careers with tech and hands-on learning. 15,000+ trained, 10,000+ placed, 20+ global partners.
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