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Data Science AI Full Stack Course - Learnees

Data Science AI Full Stack Course

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Master Data Science and AI with a full-stack approach covering Python, Machine Learning, Deep Learning, and Generative AI. Build real-world projects using data engineering, model deployment, and cloud tools. Designed to make you job-ready for high-demand AI and data roles.

Trainer :

LiveOnline Classstarts on:

Upto First 3 session - 100% Refund

1. Introduction Data Science AI Full Stack Course

Topics:

Installation of Python & IDE
Data Types
Advanced Data Types
Operators

Hands-on:

Skills You Will Learn:

2. Conditional Statements

Topics:

If
If - Else
Nested If - Else
Examples

Hands-on:

Skills You Will Learn:

3. Looping

Topics:

For
While
Nested Loops
Examples

Hands-on:

Skills You Will Learn:

4. String Manipulation

Topics:

Accessing Strings
Basic Operations
String slices
Function and Methods Examples

Hands-on:

Skills You Will Learn:

5. Lists

Topics:

Accessing list
Operations
Working with lists
Function and Methods
List comprehension

Hands-on:

Skills You Will Learn:

6. Tuple

Topics:

Accessing tuples
Operations
Working
Functions and methods
Tuple comprehension

Hands-on:

Skills You Will Learn:

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Flexible batches designed to fit your lifestyle. Select the timing that works best for you.

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JAN 24^th

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Dur: 2 months

10:00 AM (UTC)

Class Type: Weekday

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Why Choose Data Science AI Full Stack Course?

Why enroll for Data Science AI Full Stack Course Certification?

Unlock your potential in cloud computing with Data Science AI Full Stack Course certification

Most Popular Certification

Data Science AI Full Stack Course certification is rated as one of the most popular and lucrative cloud certifications in IT globally.

Growing Market

The global Data Science AI Full Stack Course market size is expected to grow at a CAGR of 21.2% from 2024 to 2030.

High Salary Potential

The estimated total pay for an Data Science AI Full Stack Course is ₹7,09,000 per year, with an average salary of ₹6,09,000 per year - Glassdoor.

Python

Machine Learning

Artificial Intelligence

Deep Learning

Tableau

SQL

Excel

Gen Al

Natural Language Processing ( NPL )

AWS ( Amazon Web Services )

Curriculum Designed by Experts

1. Introduction Data Science AI Full Stack Course

Topics:

Installation of Python & IDE
Data Types
Advanced Data Types
Operators

2. Conditional Statements

3. Looping

4. String Manipulation

5. Lists

6. Tuple

Free Career Counselling

We are happy to help you 24/7

1. Introduction Data Science AI Full Stack Course

Topics:

Installation of Python & IDE
Data Types
Advanced Data Types
Operators

Hands-on:

Skills You Will Learn:

2. Conditional Statements

Topics:

If
If - Else
Nested If - Else
Examples

Hands-on:

Skills You Will Learn:

3. Looping

Topics:

For
While
Nested Loops
Examples

Hands-on:

Skills You Will Learn:

4. String Manipulation

Topics:

Accessing Strings
Basic Operations
String slices
Function and Methods Examples

Hands-on:

Skills You Will Learn:

5. Lists

Topics:

Accessing list
Operations
Working with lists
Function and Methods
List comprehension

Hands-on:

Skills You Will Learn:

6. Tuple

Topics:

Accessing tuples
Operations
Working
Functions and methods
Tuple comprehension

Hands-on:

Skills You Will Learn:

Career Opportunities

Job roles are being prepared for this course. Please check back later.

Why Choose Inventateq

Discover the unique advantages that make our learning platform stand out

24x7 Support

One-On-One Learning Assistance
Help Desk Support
Resolve Doubts in Real-time

Hands-On Project Based Learning

Industry-Relevant Projects
Course Demo Dataset & Files
Quizzes & Assignments

Industry Recognised Certification

Learnees Training Certificate
Graded Performance Certificate
Certificate of Completion

Course Overview

Everything you need to know about Data Science AI Full Stack Course

The objective of this Data Science AI Full Stack Course is to equip learners with end-to-end skills in data analysis, machine learning, and full-stack AI application development. It aims to build strong foundations in programming, data handling, model building, and deployment so learners can create real-world, production-ready AI solutions.