If you’re curious about AI but unsure where to begin, fear not! This blog post unveils 6 of the best FREE courses to kickstart your AI adventure in 2024.
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What is AI ?
Artificial intelligence (AI) is essentially the intelligence displayed by machines, in contrast to the natural intelligence displayed by humans and animals. It’s a branch of computer science focused on creating intelligent machines capable of performing tasks that typically require human intellect.
Here are some key points about AI:
Goals: Machine learning, reasoning, and perception are all central to AI research. AI aspires to mimic human cognitive functions and surpass them in some aspects.
Applications: AI is having a significant impact on numerous sectors, from healthcare and finance to transportation and entertainment.
Types of AI: There are two main categories:
Narrow AI (Weak AI): This is the kind of AI we encounter most often. It’s skilled at performing specific tasks exceptionally well, like playing chess or recognizing faces.
General AI (Strong AI): This theoretical type of AI would possess human-level or even superior intelligence, capable of learning and adapting across various situations.
Here Are the Top 6 AI Free Courses for 2024
1. Artificial Intelligence Beginners Guide: What is AI?
Skillup’s free Artificial Intelligence course is right for you if you’re new to AI. It’s like a friendly welcome into the world of artificial intelligence, giving you a solid start.
As you dive in, we’ll guide you through important AI concepts. Have you ever wondered about the link between AI and machine learning? We’ll uncover that, too. You’ll even get to try out some practical machine-learning techniques!
By the end, you won’t just know AI; you’ll be ready for a career. This field has exciting opportunities, from working with data to creating new AI tools. And guess what? The course is completely free to access. You’ll even get a certificate to prove your achievement when you finish. Join in this hands-on journey with this free AI course from SkillUp!
Topics Covered
Introduction to AI: Basics of artificial intelligence and its applications.
AI vs. Machine Learning: Understanding the major distinctions between AI and machine learning.
Machine Learning Techniques: Explore essential ML algorithms and their practical use.
Ethics in AI: Considerations for responsible AI development and deployment.
AI in Industries: Real-world applications across diverse sectors.
Career Opportunities in AI: How AI proficiency can open doors to rewarding careers.
Practical Exercises: Apply theoretical knowledge through hands-on tasks.
Future of AI: Trends and innovations are shaping the AI landscape.
Enroll now to access this comprehensive artificial intelligence course free of charge and kickstart your learning journey with this outstanding free course on AI!
Course Link Click Here
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2. Deep Learning for Beginners
A branch of Machine Learning, deep learning deals with modelling high-level data abstractions. Deep learning can handle different data types such as images, texts, voice/sound, graphs, etc.
The free deep learning course will help you learn complex data patterns and make predictions using deep learning models. The course is ideal for beginners who can start with deep learning fundamentals and progress to advanced concepts in Deep learning. Software engineers, data scientists, data analysts, and statisticians can learn deep learning fundamentals. The course includes implementing neural components and applications of deep learning on real-world data sets.
The course’s main objective is to familiarize you with the tools and techniques to handle large data sets and uncover deep learning methods in Neural networks.
Topics Covered:
The deep learning free certification course covers the fundamentals of deep learning and its applications. The course covers topics such as Neural Networks, TensorFlow, its program elements and installation, Tensorflow Object Detection API tutorial, Deep Learning Libraries, Deep Learning Frameworks, Keras, PyTorch, and Types of Recurrent Neural Networks. It also provides frequently asked interview questions along with the topics mentioned.
Course Link Click Here
3. Machine Learning
This free machine learning course is designed to provide you with a solid foundation in machine learning, one of the most exciting and rapidly growing fields in technology and data science. Whether you’re a beginner or a machine learning professional looking to refresh your knowledge, this course is just the right one for you!
Topics Covered:
Supervised and Unsupervised Learning: We dive into the two fundamental categories of machine learning. In supervised learning, you’ll discover how models learn from labeled data, making predictions based on patterns. Unsupervised learning takes you into the world of unlabeled data, where models uncover hidden structures and relationships within the information.
Time Series Modeling: Understand how to handle data that evolves over time. Time series modelling equips you to analyze and make predictions in scenarios like stock prices, weather patterns, and more.
Linear and Logistic Regression: Master linear regression for predicting continuous outcomes and logistic regression for classification problems. These are the building blocks of predictive modelling.
Kernel SVM: Delve into Support Vector Machines with kernel functions. You’ll learn how to separate complex data using nonlinear decision boundaries.
K-Means Clustering: Discover the power of K-Means clustering to group data into clusters based on similarity, a fundamental technique in unsupervised learning.
Naive Bayes: Explore the simple yet effective Naive Bayes algorithm for classification, often used in natural language processing and spam email detection.
Decision Tree: Uncover the decision tree algorithm, which is an intuitive way to make decisions based on input features, suitable for both classification and regression tasks.
Random Forest Classifiers: Go beyond a single decision tree and understand how random forests combine multiple trees to improve accuracy and robustness.
Boosting and Bagging Techniques: Learn about ensemble methods, including boosting and bagging, which combine the strengths of multiple models to enhance predictive performance.
Deep Learning Fundamentals: Delve into the exciting world of deep learning, a subset of machine learning that focuses on neural networks with multiple layers. Explore their architecture, training, and applications in image and speech recognition, among other fields.
These topics, collectively covered in our course, equip you with a well-rounded understanding of machine learning, allowing you to tackle diverse data science challenges and leverage the power of this field in a wide range of applications.
Course Link Click Here
4. Getting Started with Machine Learning Algorithms
This free course will help you learn machine learning algorithms in great depth. You will learn supervised learning algorithms and unsupervised learning algorithms, k-means clustering, PCA, reinforcement learning, and Q-learning. By the end of this course, you will be trained in the skills essential for a skilled machine learning engineer.
Who should learn?
Machine learning enthusiasts
Software engineers
Data scientists
Data analysts
Statisticians
Course Link Click Here
5.(NLP) Text Mining Tutorial for Beginners
The Natural Language Processing and Text Mining free course gives you a detailed look into how machine learning algorithms can be applied to process large amounts of natural language data. The course explores the basics of natural language processing, text mining and helps you develop the skills required to get started on a machine learning career.
Skills you will learn
Working with Natural Language ToolKit Library
Text Extraction and Preprocessing
Structuring Sentences
Course Link Click Here
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6.TensorFlow for Beginners
This free course will help you learn TensorFlow, a popular open-source library for deep learning. Get started with TensorFlow, its basics, and how to install it on Ubuntu. Understand the nuances of the TensorFlow object detection API and how it identifies objects in images and videos.
TensorFlow Skills you will learn
Deep learning platforms
Recurrent neural networks
TensorFlow Object Detection API
Data flow graph
Linear regression using TensorFlow
Course Link Click Here
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