Grameenphone Academy

Artificial Intelligence & Machine Learning Fundamentals

Instructor

CodersTrust

Category

(Freelancing Skill)

Explore the essentials of Artificial Intelligence and Machine Learning in our course. Perfect for newcomers, this course covers core concepts, Python programming basics, and fundamental techniques like data preprocessing and model building. Through hands-on projects, you'll gain practical experience and build confidence in applying AI and ML principles. By the course's end, you'll be equipped with foundational skills to explore deeper into the exciting realms of AI and ML.

Curriculam

Course Info

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Artificial Intelligence & Machine Learning Fundamentals
|
6 hr 2 min
|
39 Lessons
|
738 Students

Our Gallery

Artificial Intelligence & Machine Learning Fundamentals

Instructor

CodersTrust

Curriculam

Artificial Intelligence & Machine Learning Fundamentals

Instructor

CodersTrust

Category

(Freelancing Skill)

Curriculam

Module 1: Course Overview

Course Overview

Module 1 Resource : Course Overview

Module 2: Introduction to AI and ML

What is Artificial Intelligence (AI)?

Different types of AI

What is Machine Learning (ML)?

Types of Machine Learning

Applications of AI and ML

AIML Module 2 Quiz

Module 2 Resource: Introduction to AI and ML

Module 3: Data Fundamentals

Role of Data in AI &amp; ML

Types of Data (structured, unstructured, semi-structured)

Data collection

Exploratory Data Analysis

Data Preprocessing

Module 3: Data Fundamentals Quiz

Module 3 Resource: Data Fundamentals

Module 4: Python for AI and ML

Introduction to Python​

Python Environment Setup​

Python Syntax​

Pandas Essentials​

Numpy Essentials​

Matplotlib Essentials​

Examples : Data Cleaning, Preprocessing and Transformation​

Module 4: Python for AI and ML Quiz

Module 4 Resource: Python for AI and ML

Module 5: Machine Learning Algorithms

Understanding Machine ​Learning Basics​

Introduction to Common Supervised Learning Algorithms​

Introduction to Common Unsupervised Learning Algorithms​

Model Evaluation Metrics​

Code Exmple : Implementing a Simple Linear Regression Model in Python​

Module 5: Machine Learning Algorithms Quiz

Module 5 Resource : Machine Learning Algorithms

Module 6: Introduction to Deep Learning

Deep Learning Fundamentals​

Neural Networks Fundamentals​

Deep Learning Architectures​

Practical Deep Learning​

Module 6: Introduction to Deep Learning Quiz

Module 6 Resource : Introduction to Deep Learning

Final Exam

Artificial Intelligence and Machine Learning Fundamentals - Final Exam

Course Info

Our Gallery

Artificial Intelligence & Machine Learning Fundamentals

Instructor

CodersTrust

Category

(Freelancing Skill)

Curriculam

Module 1: Course Overview

Course Overview

Module 1 Resource : Course Overview

Module 2: Introduction to AI and ML

What is Artificial Intelligence (AI)?

Different types of AI

What is Machine Learning (ML)?

Types of Machine Learning

Applications of AI and ML

AIML Module 2 Quiz

Module 2 Resource: Introduction to AI and ML

Module 3: Data Fundamentals

Role of Data in AI &amp; ML

Types of Data (structured, unstructured, semi-structured)

Data collection

Exploratory Data Analysis

Data Preprocessing

Module 3: Data Fundamentals Quiz

Module 3 Resource: Data Fundamentals

Module 4: Python for AI and ML

Role of Data in AI & ML

Introduction to Python

Python Environment Setup

Python Syntax

Pandas Essentials

Numpy Essentials

Matplotlib Essentials

Examples : Data Cleaning, Preprocessing and Transformation

Understanding Machine Learning Basics

Introduction to Common Supervised Learning Algorithms

Introduction to Common Unsupervised Learning Algorithms

Model Evaluation Metrics

Code Exmple : Implementing a Simple Linear Regression Model in Python

Deep Learning Fundamentals

Neural Networks Fundamentals

Deep Learning Architectures

Practical Deep Learning

Role of Data in AI & ML

Introduction to Python

Python Environment Setup

Python Syntax

Pandas Essentials

Numpy Essentials

Matplotlib Essentials

Examples : Data Cleaning, Preprocessing and Transformation

Understanding Machine Learning Basics

Introduction to Common Supervised Learning Algorithms

Introduction to Common Unsupervised Learning Algorithms

Model Evaluation Metrics

Code Exmple : Implementing a Simple Linear Regression Model in Python

Deep Learning Fundamentals

Neural Networks Fundamentals

Deep Learning Architectures

Practical Deep Learning