AI Learning Program

About Course

Course Overview

This Artificial Intelligence (AI) training program is designed to provide a comprehensive learning path from basic concepts to advanced AI techniques. You will gain hands-on experience with machine learning, deep learning, and AI applications, while mastering Python and various AI libraries. This course is ideal for anyone looking to develop a deep understanding of AI and pursue a career in this exciting field.

Course Duration

Total Duration: 12-16 weeks (depending on the learning pace).
Weekly commitment: 8-10 hours of learning.

What Will You Learn?

Gain a solid foundation in AI, including key concepts, applications, and terminologies.
Learn Python programming and explore essential libraries like NumPy, Pandas, and Matplotlib.
Master data preprocessing, machine learning algorithms, and advanced deep learning techniques.
Develop expertise in Natural Language Processing (NLP), Reinforcement Learning (RL), and model deployment.

Material Includes

Video lectures, interactive tutorials, and code-along exercises.
Hands-on projects and real-world datasets.
Access to online resources, libraries, and tools for implementation.
Comprehensive course notes and documentation.

Course Curriculum

Module 1: Foundation (Basic Concepts & Python Programming)

Introduction to AI: Learn the core concepts, types, and real-world applications of AI like self-driving cars and facial recognition.
Python Programming for AI: Master Python basics, data structures, functions, and file handling, essential for AI development.
Introduction to Data Science & Machine Learning: Understand the basics of data science and key machine learning concepts, using libraries like NumPy and pandas.

Module 2: Core Machine Learning Techniques

Module 3: Advanced Machine Learning & Introduction to Deep Learning

Module 4: Specialized AI Topics

Module 5: Final Project & Deployment

Your Instructors

kodestree

0 Rating 70 Courses 0 Students

Contact US

Follow Us

AI Learning Program

kodestree

Data Science & Analytics

March 3, 2025

About Course

What Will You Learn?

Material Includes

Course Curriculum

Module 1: Foundation (Basic Concepts & Python Programming)

Introduction to AI: Learn the core concepts, types, and real-world applications of AI like self-driving cars and facial recognition.

Python Programming for AI: Master Python basics, data structures, functions, and file handling, essential for AI development.

Introduction to Data Science & Machine Learning: Understand the basics of data science and key machine learning concepts, using libraries like NumPy and pandas.

Module 2: Core Machine Learning Techniques

Data Preprocessing: Learn how to clean data, handle missing values, and apply normalization for better machine learning performance.

Supervised Learning: Understand linear regression, logistic regression, decision trees, and SVM for predictive modeling.

Unsupervised Learning: Explore clustering methods like K-Means and hierarchical clustering, as well as dimensionality reduction techniques like PCA.

Module 3: Advanced Machine Learning & Introduction to Deep Learning

Advanced Supervised Learning: Dive into Naive Bayes, KNN, and ensemble methods like Bagging and Boosting.

Introduction to Deep Learning: Learn the fundamentals of neural networks, backpropagation, and optimization techniques like gradient descent.

Convolutional Neural Networks (CNNs): Build CNNs for tasks like image classification and object detection using deep learning frameworks.

Module 4: Specialized AI Topics

Natural Language Processing (NLP): Gain knowledge in text preprocessing, classification, word embeddings, and RNNs for sequential data.

Reinforcement Learning (RL): Understand agent-environment interactions, Q-learning, and Deep Q Networks for complex decision-making tasks.

Module 5: Final Project & Deployment

AI Project Development: Apply your skills to build end-to-end AI projects, from data collection to model evaluation.

Model Deployment and Maintenance: Learn deployment strategies using Flask/FastAPI and cloud platforms like AWS or Azure.

Ethical AI & AI for Social Good: Explore the ethical challenges in AI and learn how AI can be applied for social good in areas like healthcare and education.

Your Instructors

kodestree

This course includes:

Quick Links

Courses

Contact Us

Contact US

Follow Us

AI Learning Program

March 3, 2025

About Course

What Will You Learn?

Material Includes

Course Curriculum

Module 1: Foundation (Basic Concepts & Python Programming)

Introduction to AI: Learn the core concepts, types, and real-world applications of AI like self-driving cars and facial recognition.

Python Programming for AI: Master Python basics, data structures, functions, and file handling, essential for AI development.

Introduction to Data Science & Machine Learning: Understand the basics of data science and key machine learning concepts, using libraries like NumPy and pandas.

Module 2: Core Machine Learning Techniques

Data Preprocessing: Learn how to clean data, handle missing values, and apply normalization for better machine learning performance.

Supervised Learning: Understand linear regression, logistic regression, decision trees, and SVM for predictive modeling.

Unsupervised Learning: Explore clustering methods like K-Means and hierarchical clustering, as well as dimensionality reduction techniques like PCA.

Module 3: Advanced Machine Learning & Introduction to Deep Learning

Advanced Supervised Learning: Dive into Naive Bayes, KNN, and ensemble methods like Bagging and Boosting.

Introduction to Deep Learning: Learn the fundamentals of neural networks, backpropagation, and optimization techniques like gradient descent.

Convolutional Neural Networks (CNNs): Build CNNs for tasks like image classification and object detection using deep learning frameworks.

Module 4: Specialized AI Topics

Natural Language Processing (NLP): Gain knowledge in text preprocessing, classification, word embeddings, and RNNs for sequential data.

Reinforcement Learning (RL): Understand agent-environment interactions, Q-learning, and Deep Q Networks for complex decision-making tasks.

Module 5: Final Project & Deployment

AI Project Development: Apply your skills to build end-to-end AI projects, from data collection to model evaluation.

Model Deployment and Maintenance: Learn deployment strategies using Flask/FastAPI and cloud platforms like AWS or Azure.

Ethical AI & AI for Social Good: Explore the ethical challenges in AI and learn how AI can be applied for social good in areas like healthcare and education.

Your Instructors

kodestree

This course includes:

Related Courses

Quick Links

Courses

Contact Us