Genesis-GenAI
The Genesis course by CodeGrads is a comprehensive 4-month program that blends Python programming, data analytics, and Generative AI. Designed for beginners and professionals with or without a foundational understanding of Python, it offers instructor-led sessions culminating in a certification from National American University. The curriculum encompasses Python essentials, data exploration, visualization techniques, and hands-on experience with Generative AI applications. This course is ideal for individuals aiming to enhance their skills in AI and data science, preparing them for advanced roles in the tech industry.
₹75000.00 ₹90000.00 17% OFF
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Course Overview
Schedule of Classes
Course Curriculum
3 Subjects
GenAI
16 Exercises • 59 Learning Materials
Module 1
Preprocessing Techniques in NLP
Neural Networks
Module 2
Optimizers
Hyperparameter tuning - Neural Network
Assignment G1 and G2
G1
G2
Module 3
Attention Mechanism and it's Types
Transformers Architecture
Module 4
Bert and its Types
Auto Model
AutoTokenizer
Assignment G3 and G4
G3
G4
Module 5
Langchain and its Components
LLM Comparison
Module 6
ChatGPT with OpenAPI keys
Introduction to DeepseekR1 and its implementation
Assignment G5 and G6
G5
G6
Module 7
HuggingFace
Types of LLMs
Module 8
Fine-Tunning
Prompt Engineering
Assignment G7 and G8
G7
G8
Module 9
Code generation
Chains
Module 10
RAG Summarization
Document Loaders
Assignment G9 and G10
G9
G10
Module 11
Chunking
RAG
Module 12
Retrievers for RAG
Vector Databases
Assignment G11 and G12
G11
G12
Module 13
RAG Evaluation
Quantization
Module 14
Embedding Models
Multi Modal RAG Architecture
Assignment G13 and G14
G13
G14
Module 15
Tools and Agents
CrewAI
Module 16
LangGraph
Gradio
Assignment G15
G15
Module 17
Text-To-Image
MCP
Module 18
Agentic AI
G1
G2
G3
G4
G5
G6
G7
G8
G9
G10
G11
G12
G13
G14
Module Assessment 3
Assignment G16 and G17
Module Assessment 3
Module Assessment 3
Python
11 Exercises • 35 Learning Materials
Module 1
Data Structure
Data Types
Language Syntax
Data Structure
Data Types
Language Syntax
Module 2
Lambda functions
Notable Built-In Functions in Python
User Defined Functions
Comments Python Keywords and Identifiers
Lambda functions
Notable Built-In Functions in Python
User Defined Functions
Comments Python Keywords and Identifiers
Assignment P1, P2, P3 and P4
P1
P2
P3
P4
Module 3
For and While Loops
If Else Block
List Comprehensions
For and While Loops
If Else Block
List Comprehensions
Module 4
Error Handling
OOP Concepts
OS Library
Python Packages
Error Handling
OOP Concepts
OS Library
Python Packages
Assignment P5, P6, P7 and P8
P5
P6
P7
P8
Module 5
Threading and Parallel Processing
Understanding Date and Time
Virtual Environment
Threading and Parallel Processing
Understanding Date and Time
Virtual Environment
Assignment P9 and P10
P9
P10
Module Assessment 1
Module Assessment 1
P1
P2
P3
P4
P5
P6
P7
P8
P9
Module Assessment 1
Data Analytics
9 Exercises • 48 Learning Materials
Module 1
Pandas DataFrame and Series
Data type and Conversions
Pandas DataFrame and Series
Data type and Conversions
Module 2
Indexing and Data Selection
Pandas DataFrame Query
Indexing and Data Selection
Pandas DataFrame Query
Assignment D1 and D2
D1
D2
Module 3
Numpy
Data Exploration and Summary
Handling Missing Values
Numpy
Data Exploration and Summary
Handling Missing Values
Module 4
Duplicates and Outliers
String Manipulation
Type Conversion and Dates
Duplicates and Outliers
String Manipulation
Type Conversion and Dates
Assignment D3, D4 and D5
D3
D4
D5
Module 5
Grouping DataFrames
Merging and Concatenating Data
Pivot and Aggregation
Grouping DataFrames
Merging and Concatenating Data
Pivot and Aggregation
Module 6
Random Sampling Datapoints
Seaborn Graphs
Matplotlib
Random Sampling Datapoints
Seaborn Graphs
Matplotlib
D1
D2
D3
D4
D5
D6
D7
D8
Module Assignment 2
Assignment D6, D7 And D8
D6
D7
D8
Module Assessment 2
Module Assessment 2
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