Prompt Engineering In Telugu

Prompt Engineering in Telugu

Become a Prompt Engineer by learning for Basic to Advanced Level. If you want to learn Prompt Engineering from scratch in a short amount of time, this master's level course is for you!

Note:Recorded Content
Course Details
Community Support
Teaching Language
Mode Of Teaching
50+ Hours

Recorded Content

Life Time
Recording Content Access
Fee Stucture
Course Syllabus

In this Introduction, you will learn what will be taught in this course and benifits of this course.

  • What is Programming?
  • What is Coding?
  • Python Library
  • Python Modules
  • Python Webframework
  • Flavours of Python
  • What can Python do? 
  • Why Python? 
  • Python Syntax compared to other programming languages
  • Python Installation

  • The print statement
  • Comments
  • Python Data Structures & Data Types
  • String Operations in Python
  • Python keywords
  • Python Variables
  • Python Type Conversions
  • Simple Input & Output

  • Arithmetic operators
  • Assignment operators
  • Comparison operators &Logical operators
  • Identity operators
  • Membership operators & Output
  • Simple Output Formatting 

  • Indentation 
  • The If statement and its’ related statement 
  • An example with if and it’s related statement
  • Else
  • Nested If
  • Short Hand If
  • Short Hand If else & Continue
  • Examples for Conditional Statements

  • Defining a function
  • Calling a function
  • return statement
  • Difference between return and print
  • Arguments
  • Parameters
  • Keyword arguments
  • Arbitrary argument
  • User defined functions
  • Nested functions
  • Functions with real time examples

  • Introduction to Numpy
  • Numpy Installation
  • NumPy – Ndarray Object
  • NumPy – Data Types
  • NumPy – Array Attributes
  • NumPy – Array Creation Routines
  • NumPy – Array from Existing Data
  • Array From Numerical Ranges
  • NumPy – Indexing & Slicing
  • NumPy – Advanced Indexing
  • NumPy – Broadcasting
  • NumPy – Iterating Over Array
  • NumPy – Array Manipulation
  • NumPy – Binary Operators
  • NumPy – String Functions
  • NumPy – Mathematical Functions
  • NumPy – Arithmetic Operations
  • NumPy – Statistical Functions
  • Sort, Search & Counting Functions
  • NumPy – Byte Swapping
  • NumPy – Copies & Views
  • NumPy – Matrix Library
  • NumPy – Linear Algebra

  • Introduction to Pandas
  • Pandas Installation
  • Python Pandas – Series
  • Python Pandas – DataFrame
  • Python Pandas – Panel
  • Python Pandas – Basic Functionality
  • Descriptive Statistics
  • Function Application
  • Python Pandas – Reindexing
  • Python Pandas – Iteration
  • Python Pandas – Sorting
  • Working with Text Data
  • Options & Customization
  • Indexing & Selecting Data
  • Statistical Functions
  • Python Pandas – Window Functions
  • Python Pandas – Date Functionality
  • Python Pandas – Timedelta
  • Python Pandas – Categorical Data
  • Python Pandas – Visualization
  • Python Pandas – IO Tools

  • Matplotlib
  • Matplotlib Introduction
  • Bar Plot
  • Pie Chart
  • Histogram
  • Small Project using Matplotlib

  • Introduction to Natural language processing (NLP)
  • Introduction to Large language models (LLM)
  • Generative AI
  • Prompt Engineering
  • Applications of Prompt Engineering
  • Future with Large language models (LLM)

  • Guidelines
    • Princple 1:Instructions
    • Princple 2:Thinking Time
  • Iterative
    • Issue 1:Long Text
    • Issue 2:Wrong Details
    • Issue 3:Description Type
  • Summarizing
    • Summarize Limit
    • Categorical Summarization
    • Multiple Summarization
  • Inferring
    • Sentiment
    • Emotional Identification
  • Transforming
    • Language Translation
    • Universal Translator
    • Tone Transformation
    • Spell Check
  • Expanding
  • Customaized Reply
  • ChatBot
  • Conclusion

  • Models, Parsers
    • Templates
    • Prompts
    • Output Parsers
  • Memory
    • Conversation Buffer Memory
    • Conversation Buffer Window Memory
    • Conversation Token Buffer Memory
    • Conversation Summary Memory
  • Chains
    • LLM Chain
    • Sequential Chain
    • Router Chain
  • Q/A system
  • Evaluation
    • Example Generation
    • Manual Evaluation
    • LLM Evaluation Assistant
  • Agents
  • Conclusion
Health Assistant

This Project AI can help hospitals and clinics to identify and diagnose diseases earlier, which allows for more effective treatment. By using AI to analyze patient data and make accurate diagnoses, healthcare providers are able to provide patients with the most effective care possible.

Jarvis Assistant

This Project Jarvis AI can be implemented in various forms, such as standalone applications, integrations within existing platforms, or as part of smart devices, aiming to enhance productivity, convenience, and user experience in different domains like personal organization, business operations, customer service, and more.

Shopping Guide

This Project By implementing these steps and leveraging prompt engineering techniques, you can create a robust shopping guide assistance system powered by AI, capable of providing valuable recommendations and assistance to users in their purchasing decisions.

Order Bot

This Project Building an order bot AI involves a comprehensive approach that combines conversational design, AI technologies, integration with backend systems, and a focus on user experience to create an efficient and user-friendly ordering system.

PDF Content Reader

This Project By following these steps and leveraging prompt engineering methodologies, you can develop an AI-powered PDF converter capable of efficiently handling diverse document formats and converting them into high-quality PDF files based on user instructions.

Text to Image Generator

This Project By following these steps and employing prompt engineering methods, you can build a Text to Image Generator AI system capable of translating textual descriptions into corresponding visual representations effectively.

What We Provide
Watch Demo Class now in Telugu

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Frequently Asked Questions

The education offered by Python Life is industrial education. We are known for our course programs. And whatever we teach, it starts from scratch to advanced level. An experienced instructor is available to him 24/7 to clear any doubts.

Yes, all concepts are taught from basic to advanced level and the instructor will check if students understand before moving on to more subjects.

Of course, Python Life trains students according to industry requirements and specifications. We also conduct in-house planning and mock interviews.

There are no eligibility criteria for this course, which is taught from start to finish, so anyone interested in the course can participate.

Yes, you will receive a course completion certificate from Python Life when you submit your project at the end of the course.

Sorry, No refunds.

You can join by paying from our site. Immediately after payment, you will receive a confirmation from us to guide you through the further process.

Yes, all sessions will be recorded and will be provided for the students.