10-22-2024, 12:39 AM
7 Days of Hands-On AI Development Bootcamp
From Zero to AI: A Beginner's Guide to Building and Deploying AI Projects
Rating: 0.0 out of 5
(0 ratings)
800 students
4 hours on-demand video
Assignments
Description
Welcome to "7 Days of Hands-On AI Development Bootcamp: Build Real-World AI Projects from Scratch," a course designed for absolute beginners who are eager to step into the world of artificial intelligence (AI). This course is ideal for those with little to no prior experience in programming or AI but have the curiosity and drive to learn. Whether you're a student, a career-changer, or simply interested in building your first AI project, this course is structured to take you from zero knowledge to deploying real-world AI models.
Over the span of 7 days, you’ll build projects every day, starting from the basics of Python programming to deploying a fully-functional AI model on the web. Each day is packed with hands-on projects, practical applications, and easy-to-follow instructions to ensure that you gain not just theoretical knowledge but real-world skills that you can apply right away.
What You Will Learn:
This course covers everything you need to get started with AI development. Each day is focused on a new topic, gradually building on what you’ve learned previously. Here’s a brief overview of what you can expect:
Day 1: Python for AI Basics
We start with the foundation—Python programming. Python is the most popular language for AI, and by the end of Day 1, you’ll understand basic Python syntax, data types, control flow, and how to use essential libraries like NumPy and Pandas. You’ll also build your first simple program, setting the stage for the AI projects to come.
Day 2: Exploratory Data Analysis (EDA)
Data is the backbone of AI, and before you can train models, you need to know how to analyze it. On Day 2, you will learn how to clean, manipulate, and visualize data. Using libraries like Matplotlib and Seaborn, you’ll explore datasets, handle missing data, and visualize relationships between different features. You’ll work with real-world data to uncover hidden insights.
Day 3: Introduction to Machine Learning
On Day 3, we dive into machine learning with a focus on Linear Regression. You’ll learn the fundamentals of supervised learning, including how to split your dataset into training and testing sets, train a model, and evaluate its performance. By the end of the day, you’ll build your first predictive model to forecast continuous variables like house prices.
Day 4: Classification Models in Machine Learning
Next, you’ll tackle classification problems using Logistic Regression. Whether predicting if an email is spam or classifying customer churn, this day teaches you how to build a classification model and evaluate it using metrics like precision, recall, and accuracy. You’ll also learn how to interpret confusion matrices to understand the performance of your model.
Day 5: Neural Networks and Deep Learning
Day 5 introduces the fascinating world of neural networks. You’ll build a simple feedforward neural network to classify handwritten digits using the MNIST dataset. You’ll gain hands-on experience with libraries like TensorFlow or PyTorch, and learn about key concepts such as activation functions, backpropagation, and training deep learning models.
Day 6: Natural Language Processing (NLP)
Day 6 focuses on Natural Language Processing (NLP), where you’ll build a sentiment analysis model using text data. By leveraging pre-trained models from Hugging Face or building your own with TensorFlow, you’ll classify text as positive or negative. This day provides an introduction to text preprocessing, tokenization, and transfer learning in NLP.
Day 7: Deploying an AI Model as a Web Service
On the final day, you’ll learn how to deploy your AI models as a web service using Flask. You’ll integrate your AI models into a web application, making them accessible to users via a browser. Additionally, you’ll deploy your app to a cloud platform like Heroku. By the end of the day, you’ll have a working AI-powered web app that anyone can interact with online.
https://www.udemy.com/course/7-days-of-hands-on-ai-development-bootcamp/?couponCode=B6B33FD70B8B25EDB570
Enjoy!
From Zero to AI: A Beginner's Guide to Building and Deploying AI Projects
Rating: 0.0 out of 5
(0 ratings)
800 students
4 hours on-demand video
Assignments
Description
Welcome to "7 Days of Hands-On AI Development Bootcamp: Build Real-World AI Projects from Scratch," a course designed for absolute beginners who are eager to step into the world of artificial intelligence (AI). This course is ideal for those with little to no prior experience in programming or AI but have the curiosity and drive to learn. Whether you're a student, a career-changer, or simply interested in building your first AI project, this course is structured to take you from zero knowledge to deploying real-world AI models.
Over the span of 7 days, you’ll build projects every day, starting from the basics of Python programming to deploying a fully-functional AI model on the web. Each day is packed with hands-on projects, practical applications, and easy-to-follow instructions to ensure that you gain not just theoretical knowledge but real-world skills that you can apply right away.
What You Will Learn:
This course covers everything you need to get started with AI development. Each day is focused on a new topic, gradually building on what you’ve learned previously. Here’s a brief overview of what you can expect:
Day 1: Python for AI Basics
We start with the foundation—Python programming. Python is the most popular language for AI, and by the end of Day 1, you’ll understand basic Python syntax, data types, control flow, and how to use essential libraries like NumPy and Pandas. You’ll also build your first simple program, setting the stage for the AI projects to come.
Day 2: Exploratory Data Analysis (EDA)
Data is the backbone of AI, and before you can train models, you need to know how to analyze it. On Day 2, you will learn how to clean, manipulate, and visualize data. Using libraries like Matplotlib and Seaborn, you’ll explore datasets, handle missing data, and visualize relationships between different features. You’ll work with real-world data to uncover hidden insights.
Day 3: Introduction to Machine Learning
On Day 3, we dive into machine learning with a focus on Linear Regression. You’ll learn the fundamentals of supervised learning, including how to split your dataset into training and testing sets, train a model, and evaluate its performance. By the end of the day, you’ll build your first predictive model to forecast continuous variables like house prices.
Day 4: Classification Models in Machine Learning
Next, you’ll tackle classification problems using Logistic Regression. Whether predicting if an email is spam or classifying customer churn, this day teaches you how to build a classification model and evaluate it using metrics like precision, recall, and accuracy. You’ll also learn how to interpret confusion matrices to understand the performance of your model.
Day 5: Neural Networks and Deep Learning
Day 5 introduces the fascinating world of neural networks. You’ll build a simple feedforward neural network to classify handwritten digits using the MNIST dataset. You’ll gain hands-on experience with libraries like TensorFlow or PyTorch, and learn about key concepts such as activation functions, backpropagation, and training deep learning models.
Day 6: Natural Language Processing (NLP)
Day 6 focuses on Natural Language Processing (NLP), where you’ll build a sentiment analysis model using text data. By leveraging pre-trained models from Hugging Face or building your own with TensorFlow, you’ll classify text as positive or negative. This day provides an introduction to text preprocessing, tokenization, and transfer learning in NLP.
Day 7: Deploying an AI Model as a Web Service
On the final day, you’ll learn how to deploy your AI models as a web service using Flask. You’ll integrate your AI models into a web application, making them accessible to users via a browser. Additionally, you’ll deploy your app to a cloud platform like Heroku. By the end of the day, you’ll have a working AI-powered web app that anyone can interact with online.
https://www.udemy.com/course/7-days-of-hands-on-ai-development-bootcamp/?couponCode=B6B33FD70B8B25EDB570
Enjoy!