Prompt Engineering Course in Hyderabad

1. Introduction to prompt engineering.
2. what is prompt
3. what is response
4. Introduction to chat-gpt
5. Other AI tools similar to chat-gpt like bard, bing .
6. What is Artificial Intelligence
7. Introduction to Machine learning
8. Types of Machine Learning
-> Supervised Learning
-> Unsupervised learning
-> Reinforcement Learning.
9. Introduction to Neural Networks.
10.Introduction to Deep Learning.
11. Types of Deep learning .
-> Descriminative models
-> Generative models
10. Introduction to NLP (Natural Language Processing).
11. NLP with Machine Learning
12. NLP with Deep Learning.
13. LLM (Large language Modeling) introduction.
14. difference between NLP and LLM
15. Introduction to Generative AI.
16. Generative AI applications.
17. Generative AI use cases.
18. Major tasks in prompt engineering as below.
-> prompt to Text content
-> prompt to Image generation
-> prompt to Audio generation
-> prompt to video generation
-> prompt to task execution.
19. many tools available in market, what does prompt
engineer has to do ?
20. prompt engineering challenges.
21. Summary of this module.

1. Basics of Python Programming :
   ● Installation and Setup:
   ● Installing Python and setting up a development environment (IDEs
   like PyCharm, VSCode, Jupyter Notebooks)
   ● Syntax and Basic Constructs:
   ● Variables and data types (integers, floats, strings, booleans)
   ● Basic input and output
   ● Comments and documentation
2. Control Structures:
   ● Conditional Statements:
   ● if, elif, else
   ● Loops:
   ● for, while
   ● Loop control statements (break, continue, pass)
3. Functions:
   ● Defining Functions:
   ● Parameters and return values
   ● Scope and Lifetime:
   ● Local and global variables
   ● Lambda Functions:
   ● Anonymous functions

Core Data Structures

1. Lists:
   ● Creating, accessing, modifying, and iterating over lists
   ● List comprehensions
2. Tuples:
   ● Creating and using tuples
   ● Unpacking tuples
3. Sets:
   ● Creating and using sets
   ● Set operations (union, intersection, difference)
4. Dictionaries:
   ● Creating and using dictionaries
   ● Dictionary methods and comprehensions

Advanced Data Structures

1.Collections Module:
● defaultdict, Counter, OrderedDict, deque

1. Reading and Writing Files:
   ● Opening, reading, writing, and closing files
   ● Working with different file modes (r, w, a, rb, wb)
2. Working with CSV and JSON:
   ● Reading from and writing to CSV and JSON files using csv and json
   modules

1. Classes and Objects:
   ● Defining classes and creating objects
   ● Instance variables and methods
2. Class Variables and Methods:
   ● Using class variables and class methods
3. Inheritance:
   ● Single and multiple inheritance
4. Polymorphism and Encapsulation:
   ● Method overriding
   ● Private variables and name mangling

1. Creating and Importing Modules:
   ● Defining and using modules
2. Packages:
   ● Organizing code into packages
   ● Importing from packages

Error Handling

1. Exception Types:
   ● Common exceptions (ValueError, TypeError, etc.,)
2. Try, Except Blocks:
   ● Using try, except, else, and finally
3. Custom Exceptions:
   ● Creating and raising custom exception

Debugging
1. Debugging Techniques:
● Using print statements and logging
● Using debuggers (pdb)

1. Decorators:
   ● Function decorators
   ● Class decorators
2. Context Managers:
   ● Using with statement
   ● Creating custom context managers with __enter__ and __exit__

1. Iterators:
   ● Creating iterators using __iter__ and __next__
2. Generators:
   ● Creating generators with yield
   ● Generator expressions

1. NumPy:
   ● Arrays and matrix operations
2. Pandas:
   ● DataFrames for data manipulation
   ● Reading and writing data (CSV, Excel)

1. Matplotlib:
   ● Plotting graphs and charts
2. Seaborn:
   ● Statistical data visualization

1. Unittest Framework:
   ● Writing and running tests
   ● Test fixtures and test suites
2. Pytest:
   ● Advanced testing with pytest