Machine Learning is one of the most promising careers in the twenty-first century. It has a large number of high-paying work possibilities, therefore the need for Machine Learning Courses has been rising. Furthermore, the future scope of Machine Learning is on its way to radically alter the world of automation. Machine Learning also has a lot of potential in India. As a result, you can make a good living in the field of Machine Learning and contribute to the digital world’s growth.
Let us know look at 10 Best Machine Learning Courses for freshers!
About Machine Learning
Let us begin by getting an overview about Machine Learning. Artificial Intelligence has a subfield called Machine Learning. It aids in the development of self-learning automated systems. The system then improves their performance by learning from their mistakes without the need for human intervention. This aids the machines in making data-driven decisions.
Machines employ what they’ve learned from previous experience and accessible data to generate predictions. You must have used Google Maps for navigation, for example. It attempts to show the quickest route with the least amount of traffic and congestion. Machine Learning methods are used to complete this task.
We shall now move towards 10 Best Machine Learning Courses especially for freshers that will help them in securing a job along with getting an edge over others!
10 Best Machine Learning Courses for getting a fresher job
These days, machine learning is the most popular field in computer science! It is one of the newest technologies, with many companies from many industries using it. If you wish to learn this technology, it’s no surprise. But don’t worry if you don’t want to go to university since you’re a working professional or don’t want to spend a lot of money on a degree. Many online courses from the world’s greatest universities, taught by notable experts, are available on sites such as Coursera, edX, Udemy, and others, Some of them are –
- Firstly, Vskills’ Certified Machine Learning (Python) Professional
- Secondly, Machine Learning by Stanford University (Coursera)
- Furthermore, Data Science: Machine Learning (Harvard University)
- Additionally, Deep Learning Specialization by deeplearning.ai (Coursera)
- Moreover, Machine Learning with Python by IBM (Coursera)
- In addition, Machine Learning Specialization by University of Washington (Coursera)
- Furthermore, Advanced Machine learning Specialization (Coursera)
- Also, Introduction to Machine Learning Course (Udacity)
- Additionally, Introduction to Machine Learning for Coders (University of San Francisco)
- Lastly, Intro to Machine Learning with PyTorch (Udacity)
Let us now dive deeper into each one of them!
Vskills’ Certified Machine Learning (Python) Professional
Machine learning has always been a vital area of computer science, but recent advances in processor power and algorithm efficiency have elevated it to new heights. Vskills certification in Machine Learning evaluates the candidate in light of the company’s Machine Learning requirements. You will study about Supervised Learning, Supervised Learning Models, Unsupervised Learning, Neural Networks, and Machine Learning Applications in this course. You’ll also learn and explore machine learning’s essential techniques, as well as how to use machine learning to address a variety of issues.
Machine Learning by Stanford University (Coursera)
This is the internet’s most well-known Machine Learning course! This course, taught by Andrew Ng, former Chief Scientist of Baidu and Director of the Google Brain Deep Learning Project, attempts to educate both the theoretical and practical aspects of Machine Learning algorithms. This Machine Learning course teaches you how to use Octave or MATLAB to learn Linear Regression with One Variable, Linear Regression with Multiple Variables, Logistic Regression, Regularization, Neural Networks, Support Vector Machines, Unsupervised Learning, and more. This course may be completed in 11 weeks and covers a wide range of Machine Learning topics and applications.
Data Science: Machine Learning (Harvard University)
This specialization, offered by Harvard University, is designed to assist candidates in studying machine learning and the technological issues that come with it. Unlike other courses, this one will allow you to go further into Machine Learning’s data science approaches. The program also teaches you how to work with training data and how to efficiently use a data set to find predictive associations. When you enroll in this course, you’ll learn how to use machine learning in a variety of products, including speech recognition, postal service, spam detectors, and more.
Deep Learning Specialization by deeplearning.ai (Coursera)
After you’ve completed Andrew Ng’s Machine Learning course, you can take this advanced Deep Learning specialty. Convolutional networks, recurrent neural networks, and other subjects in deep learning will be covered in this course. Many renowned leaders will share personal tales and career guidance in this session. Neural Networks and Deep Learning, Improving Deep Neural Networks, Structuring Machine Learning Projects, Convolutional Neural Networks, and Sequence Models are among the five courses in this Deep Learning specialisation. Deep learning models will be created in a variety of disciplines, including autonomous driving, healthcare, natural language processing, music production, and so on.
Machine Learning with Python by IBM (Coursera)
This course will show you how to use Python to learn Machine Learning. You will first master the fundamentals of Machine Learning and how it is used in the real world, before moving on to Machine Learning techniques like as regression, classification, and clustering. The course is divided into six weeks, with each week focusing on an Introduction to Machine Learning, Regression algorithms such as Linear, Non-linear, Simple and Multiple Regression, Clustering algorithms such as Hierarchical Clustering, Partitioned-based Clustering, and Density-based Clustering, Recommender Systems, and a Final Project utilizing everything you’ve learned.
Machine Learning Specialization by University of Washington (Coursera)
This Machine Learning Specialization will educate you about Regression algorithms, Classification algorithms, Clustering algorithms, Information Retrieval, and more utilizing theoretical knowledge and actual case studies. As a result, this Specialization will teach you how to use Machine Learning to construct intelligent apps, analyze massive datasets, and more. Machine Learning Foundations, Regression taught using a case study on predicting housing prices, Classification taught using a case study on sentiment analysis, and Clustering & Retrieval taught using a case study on similar document finding are the four courses that make up this Specialization. This specialization will take approximately 7 months to complete.
Advanced Machine learning Specialization (Coursera)
This course will teach you how to use advanced Artificial Intelligence techniques to programme computers to interact, analyse, and solve issues. You’ll learn about the inner workings of AI technologies, which are used to create today’s AI models. Students can apply for advanced machine learning positions to design projects to solve real-world challenges after completing the course. These methods can also be used to create AI models that are progressive.
Introduction to Machine Learning Course (Udacity)
This Machine Learning curriculum will teach you how to grasp the subject’s key disciplines, such as statistics and computer science, in order to maximize the predictive capacity of the technology. It’s an excellent course for aspiring data scientists, analysts, and others interested in a career in the industry. Through the lens of machine learning, you’ll learn about the specifics of data investigation procedures. You’ll also discover how to extract and recognise essential Machine Learning features for the most accurate data representation. Through its professionally prepared content, the course provides applicants with a rich learning experience.
Introduction to Machine Learning for Coders (University of San Francisco)
This course teaches students the fundamentals of machine learning from the ground up, ensuring that they have a full understanding of both the theoretical and practical applications of machine learning models. Students will be able to construct their own Machine Learning Models for commercial purposes. Also, they will utilise practical knowledge to further their technical analysis careers after completing the course. You will learn about the Random Forest, including an introduction and in-depth knowledge, model validation applications, learning model interpretation, tree interpreters, data products, and gradient descent, among other things.
Intro to Machine Learning with PyTorch (Udacity)
This Nanodegree program, which is available through Udacity, is a great way to improve your abilities and understanding in supervised models, data cleansing, and machine learning techniques. Candidates can also learn about essential areas such as unsupervised and deep learning. The course has several sections, each of which provides learners with practical experience. This allows them to put their skills to the test through coding projects and exercises. The specialization provides applicants with real-world project experience, allowing them to learn how to develop immersive content for top-tier enterprises. The learners are also lead the way for various training sessions, interview preparation, professional profile maintenance, and other crucial areas for career growth.
These were the 10 Best Machine Learning Courses for getting a fresher job. We hope this article helped you to choose the best certification matching your needs.
