7 Courses and Certifications

Edx Machine Learning Courses & Certifications

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Machine Learning

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Certificate

Machine Learning

Machine Learning is a highly in-demand curriculum for this generation. Machine Learning gives computers the ability to learn from experience without being programmed explicitly. EdX’s Machine Learning certification course is concerned with both the theoretical and practical aspects. The curriculum will present the candidates with statistical unsupervised and supervised learning methods for data remodeling and data analysis.

Georgia Institute of Technology offers the Machine Learning online course by EdX, and the university’s Executive Associate Dean Charles Isbell teaches the programme. It is an intermediate-level course that covers various theoretical concepts like the Inductive bias, the minimum description length principle, Ockham’s razor, etc. The training includes several projects and programming assignments for candidates to get a more concrete understanding of the topics. 

Students learn about various topics such as randomised search algorithms, reinforcement learning, Bayesian learning methods, etc.  After completing the Machine Learning training, the candidates will get three credits and a certificate of completion after paying the fee for certification. It will take around 14 weeks to complete the programme, and classes will be conducted online through video lectures. 

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14 Weeks
Intermediate
Free
Skills Covered:
Machine learning
Certificate

Machine Learning

Machine learning certification course by edX primary stage starts from the core development of computer programs that can acquire data and use it to learn for themselves. The course served by edx will guide the candidate through various topics that include, matrix factorization, classification and regression, topic modelling,  sequential models, clustering methods, and model selection. In the first half of the course, we will cover guided learning techniques for regression and classification. 

We will explore several fundamental methods which will be essential for performing this task and optimizing it with algorithms. In the second half of the Machine learning training course, we will shift to unguided learning techniques, where the end output will be more unpredictable based on a corresponding input. Any student or professional with knowledge of undergraduate probability, statistics, linear algebra, calculus, probability, and statistical concepts can enroll in this course. The course has a tenure of 12 weeks, where only 8-10 hours per week can push the candidate towards excellence. Under the guidance of ColumbiaX (Columbia University) after successful completion, every student will get a verified certificate with the institution's logo.

Also Read: Machine Learning Practical Applications

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12 Weeks
Expert
Free
Skills Covered:
Machine learning
Machine Learning Fundamentals

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Certificate

Machine Learning Fundamentals

In the Machine Learning Fundamentals certification course by edX using real-world problem statements students will learn to figure out the features of topics in the corpus, classify the given images, group people according to various profiles depending on their personality and also capture the semantic structure of words available. With the information learnt in the Machine Learning Fundamentals training, the students will learn to analyze different types of data and also they will be able to build predictive and descriptive models. The Machine Learning Fundamentals certification has the following included in its curriculum- conditioned probability, linear models, random forests, reduction, bagging, and many other topics that deal with the domain of machine learning

The examples that will be provided in the Machine Learning Fundamentals programme will be in the language of Python and will use Jupyter Notebooks. The candidates will also be practising various types of algorithms using data science and its applied tools. The Machine Learning Fundamentals online course will provide students with both discriminative and generative models. There are 2 tracks namely the audit track and the verified track into which the candidates may enroll. The candidates may access the course for a lifetime by paying a fee which is called the verified track, and the audit track asks for no fees but offers limited period access to the course.

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10 Weeks
Expert
Free
Skills Covered:
Machine learning
Certificate

Quantum Machine Learning

Artificial intelligence and machine learning advances run hand in hand with the degree to which quantum computing footprint improves. Thus, it is natural to leverage machine learning capabilities with the advent of quantum computing. This Quantum Machine Learning certification course will explore the underlying principles associated with futuristic technologies. 

The program on Quantum Machine Learning encompasses the advantages of machine learning once it is coupled with futuristic quantum technologies. These have the potential to provide the much-awaited advancements of this industry. Some examples include machine learning and select frameworks in Python. 

This Quantum Machine Learning training program is intended to be delivered across 9 weeks along with an input of 6-8 hours per week by the participants on their own time for optimum results. The University of Toronto is the partner institution for this self-paced course. The video transcripts are in English and the students have an option to get a paid plus official certification. 

The candidates who enroll in any track of the course will be able to progress at their speed. Both tracks - audit and verified may be opted for by the candidates for finishing the course. If the candidates are interested in learning for free without a certificate they may choose the audit track which is open for a limited period of access. For unlimited access, the students should switch over to the verified track by paying some fees.

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9 Weeks
Expert
Free
Skills Covered:
Machine learning Knowledge of Python
Classical Machine Learning for Financial Engineering

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NYU via Edx
Certificate

Classical Machine Learning for Financial Engineering

7 Weeks
Intermediate
62,443
PyTorch Basics for Machine Learning

Offered by

IBM via Edx
Certificate

PyTorch Basics for Machine Learning

The PyTorch Basics for Machine Learning certification programme is offered by IBM to arm you with the skills for implementing classic machine learning algorithms. You will get to know how PyTorch is used to optimise and create deep learning models. 

During the PyTorch Basics for Machine Learning training, you will learn important models such as linear and logistic regression models. This introductory-level programme will teach you how to train your models and their related concepts like gradient descent, cost and loss.

With the learnings of edX’s PyTorch Basics for Machine Learning course, you will learn to save your training and model in apps like checkpoints, early stopping and cross-validation for hyperparameter selection. Also, basics around the linear object, like their interaction with data with a distinctive number of samples and different dimensions, will be cleared.

The PyTorch Basics for Machine Learning course also includes a final project in the end to assess your skills and performance. You can even get a paid instructor-signed certification after completing the course. The learners also can audit the self-paced programme without paying the fee for a limited duration. 

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5 Weeks
Beginner
Free
Skills Covered:
Machine learning Knowledge of deep learning Knowledge of Numpy
Amazon SageMaker Simplifying Machine Learning Application Development

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Certificate

Amazon SageMaker: Simplifying Machine Learning Application Development

Amazon Web Services (AWS) is offering the Amazon SageMaker: Simplifying Machine Learning Application Development certification course. It will act as your guide for using Amazon SageMaker for the integration of ML or machine learning into your apps. Machine learning has surfaced as one of the most sought-after technological domains in recent times. Thus, the course can help you develop your skill-set in just a span of 4 weeks.

The Amazon SageMaker online course by edX will empower you with the knowledge of training a model with the help of a Jupyter Notebook. You will learn under the able guidance of AWS Training and Certification expert educators. Furthermore, you will have the assistance of video lectures, hands-on exercises, and demos to help you achieve fluency in the course concepts.

Moreover, the Amazon SageMaker training will allow you to hone your prior skills and help you gain new ones. You will have improved career opportunities at hand after completing this course. Although it is free of charge programme, you need to purchase the Verified Certificate track to access graded assessments and the programme certificate.

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4 Weeks
Intermediate
Free
Skills Covered:
Machine learning Knowledge of Amazon Web Services

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