Foundations of Artificial Intelligence 2025
The Fundamental concepts of AI, including Descriptive Statistics, Machine learning fundamentals, and SQL skills.
Development ,Data Science,Artificial Intelligence
Lectures -136
Resources -4
Quizzes -1
Duration -18 hours
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Course Description
Welcome to the "Foundations of Artificial Intelligence" course! This journey will take you through the essential concepts and techniques that form the backbone of artificial intelligence. This course is meticulously designed to equip learners with foundational skills and knowledge required for understanding and applying AI in various contexts.
In this course, you'll start with an introduction to Python, one of the most versatile programming languages in the AI domain. We'll guide you through the fundamental concepts of AI, including descriptive statistics, machine learning fundamentals, and SQL skills. You'll gain hands-on experience in implementing both supervised and unsupervised learning algorithms, preparing you for advanced AI courses and applications.
Tailored for students and professionals seeking to enter the field of AI, this course aims to build a strong foundation in artificial intelligence concepts and techniques. You will learn to write and understand Python code for data analysis and manipulation, utilize descriptive statistics to summarize and interpret data, and implement basic machine learning algorithms. Additionally, you will acquire SQL skills to query databases and extract meaningful insights. By the end of this course, you will be well-prepared for advanced AI studies and real-world applications, equipped with the essential knowledge and practical experience to confidently tackle AI challenges.
Goals
Python Proficiency: Write and understand Python code, and use it for data analysis and manipulation.
Descriptive Statistics: Apply statistical concepts to summarise and interpret data effectively.
Machine Learning Fundamentals: Gain a foundational understanding of machine learning concepts, with hands-on experience in implementing both
supervised and unsupervised learning algorithms.SQL Skills: Use SQL to query databases, extract meaningful insights, and manipulate data.
AI Readiness: Have the foundational knowledge required to pursue advanced AI courses and applications.
Prerequisites
Fundamental computer skills: Comfort with installing and using software.
Basic understanding of Python programming.
Essential math and statistics knowledge.

Curriculum
Check out the detailed breakdown of what’s inside the course
Python IDE's and Google Collab (Python)
4 Lectures
-
Google Collab-Part 1 17:36 17:36
-
Google Collab-Part 2 04:43 04:43
-
Anaconda Installation 06:53 06:53
-
Jupyter notebook install 05:33 05:33
Python and it's importance in modern day
2 Lectures

Data Types
5 Lectures

Operators
3 Lectures

Expressions
1 Lectures

Simple if, if-Else, nested if-Else, if-Elif-Else
3 Lectures

Control structures: iterative control structures ( for and while loop )
4 Lectures

String indexing, accessing and strings using for loop
2 Lectures

Break and continue statements
1 Lectures

Functions and types of arguments
6 Lectures

Recursion
4 Lectures

Collections: lists list functions
5 Lectures

Collections: dictionary
4 Lectures

Collections: tuples and sets
8 Lectures

Data and statistics (Descriptive Statistics)
3 Lectures

Sample & population
1 Lectures

Sampling techniques
1 Lectures

Numerical (continuous and discrete) and categorical
1 Lectures

Measures of central tendency
1 Lectures

Measures of dispersion
1 Lectures

Important terminology
5 Lectures

Normal distribution & central limit theorem
1 Lectures

Correlation
1 Lectures

Z test t test anova and chi-squared test
8 Lectures

Statistical Model using Python
1 Lectures

Probability
2 Lectures

Supervised Learning (Machine Learning)
2 Lectures

Decision Tree
4 Lectures

Random Forest
4 Lectures

KNN
4 Lectures

SVM
4 Lectures

Neural Networks
1 Lectures

Ensemble Methods
1 Lectures

Unsupervised Learning
1 Lectures

Clustering
2 Lectures

Dimensionality Reduction using PCA
2 Lectures

Association Rules
5 Lectures

Introduction to DataBases (SQL)
1 Lectures

Installation
2 Lectures

Database schema
4 Lectures

String Functions
1 Lectures

Numeric and Temporal functions
1 Lectures

SQL functions
5 Lectures

SQL Joins
5 Lectures

Union
1 Lectures

Database normalization
3 Lectures

Clustered and non clustered index
1 Lectures

SQL views
4 Lectures

Instructor Details

GreyCampus Inc.
About me
GreyCampus helps people power their careers through skills and certifications. We believe continuous upskilling and certifications is key to sustained success in your career. While older skills are fast becoming less relevant, need for newer in-demand skills is growing exponentially. We believe if you stay skilled, you will stay ahead.
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