Machine learning skills are in high demand, according to recent research. This is due to the growing importance of machine learning in various fields, including healthcare, finance, and manufacturing. Upskilling and free machine learning courses can help you keep up with industry standards.
This article is for you if you want to get into machine learning but don’t know where to begin. Free machine learning courses are available to help you get started.
Machine Learning Courses You Can Take For Free
Machine learning’s popularity has exploded in recent years. Free machine learning courses may help you advance in your job by enhancing your skills. This selection of free online courses on machine learning can help you learn more about the field and improve your existing abilities. Let’s get started now!
1. Fundamentals of Machine Learning
There are several sectors where machine learning is being employed nowadays. Machine learning is utilized in many applications, from recommendation systems to spam filtering. Businesses may gain a competitive advantage by making sense of the ever-increasing quantity of data accessible. These free machine learning courses will teach you the foundations you need to know to get started in the area.
2. Python for Machine Learning
As one of the most widely used programming languages, Python is known for its high-level syntax and ease of usage. Regarding Machine Learning, Python is a vital programming language to have on hand. Starting with NumPy, we’ll learn how to use Python for machine learning in this free on-demand online course. We’ll also learn about a Python module called Pandas, which is a fundamental part of the language.
3. Statistics for Machine Learning
Data collection, analysis, interpretation, presentation, and organization are all part of the field of statistics. Machine learning may benefit from using statistics to build a solid basis for analysis. This free online statistics for machine learning course covers the fundamentals of descriptive statistics and data visualization.
4. Machine Learning Algorithms
Modern businesses increasingly rely on artificial intelligence (AI) and machine learning. Machine learning models that have been fine-tuned have the potential to be very potent and effective in solving issues. However, this is only feasible when data is provided to the algorithms. Understanding machine learning algorithms can help you apply ideas like supervised learning to unsupervised learning more effectively.
5. Machine Learning in Finance
As we all know, machine learning has become a common practice in practically all industries. We can improve operational efficiency in various financial areas, from risk management and trading to insurance underwriting, by adopting machine learning. The application of machine learning in financial services has produced several advantages. If you are interested in learning more about the many applications of machine learning in finance, this free online course is for you! Beginners who want to learn more about the topic should take this course.
6. K-means Unsupervised Machine Learning
Unlabeled datasets are often subjected to analysis using the k-means method. It’s common practice in artificial intelligence to use unsupervised learning. If you want to learn how to do unsupervised learning with k-means, this free online course will teach you how to use NumPy, pandas, and sci-kit-learn models like k-means clustering.
7. Supervised Machine Learning using Logistic Regression and Nave Bayes
The process of teaching a computer to detect patterns using a training dataset is supervised machine learning. Each time a training data set is submitted to the machine, it receives feedback on its performance from its supervisor. In this free online course on supervised machine learning using logistic regression and naive Bayes, you will learn about logistic regression and naive Bayes algorithms.
8. Python Machine Learning Libraries
You may execute certain tasks in your Python code using libraries, which are just collections of modules. Examples include modules for performing mathematical operations in the math library. Learn about some of the most often used Python libraries, such as pandas, NumPy, seaborn, and Matplotlib, in this free Python libraries for machine learning course.
9. Machine Learning Interview Questions and Answers
To help you prepare for your future machine learning interview, we’ve included this free interview course! Taking this course will help you become more familiar with the interview questions you might anticipate encountering. You’ll be able to brush up on your machine learning fundamentals and snag the job of your dreams.
10. Supervised Machine Learning Using Tree-Based Models
Tree-based classifiers may be used to get insights from raw data and make significant judgments. This free online course on supervised machine learning using tree-based models was developed to help you better grasp the value of tree-based categorization models. Guided learning methods like random forests and decision trees are covered, as well as how to put them into practice in Python.
11. AWS Machine Learning Introduction
This free AWS machine learning course is intended for those new to the field. It’s an introduction to cloud computing, covering everything from the purposes of cloud computing to the different cloud providers to the meaning of AWS. You will thoroughly grasp the relationship between AWS and machine learning. The conclusion will learn data science, machine learning, cloud computing, and AWS services of the course.
The Final Words
Machine Learning professionals are in great demand. Free machine learning courses may help you advance your career and earn more money. There are postgraduate machine learning programs that may give you a deeper grasp of the theories and methods used in this field.