List of Online Courses and Certifications

The Practical Machine Learning with Tensorflow certification course offers a comprehensive curriculum that covers the key aspects of Tensorflow and Machine Learning such as data input, Tensorflow preprocessing, and prediction. This certification course lasts 8 weeks, and its prerequisites are Programming, Data Mining, Machine Learning, or Data Science. 

The students gain hands-on training in the subject from industry experts. The Practical Machine Learning with Tensorflow certification by NPTEL equips students with the required skills and knowledge to build ML models using Tensorflow. The candidates also learn the application of techniques, principles, and strategies in real-world projects.

Also Read: Online Machine Learning Courses & Certifications

Jure Leskovec, Jeff Ullman, and Anand Rajaraman, professors at Stanford University, wrote the book Mining of Massive Datasets. They also happen to be the instructors for the Mining Massive Datasets programme, for which their book is the source material.

The Mining Massive Datasets certification syllabus corresponds to the CS246 programme at Stanford University. The major topics covered under the curriculum include algorithms for data streams, locality-sensitive hashing, MapReduce systems and algorithms, machine-learning algorithms, frequent itemset analysis, PageRank and web-link analysis, clustering, computational advertising, dimensionality reduction, social-network graphs, and recommendation systems.

The Mining Massive Datasets online course is a seven-week advanced computer science programme. The video lectures are in English, and you can study them in your time. English transcripts are also available to help you follow along. You need to spend anywhere between five and ten hours on the programme if you want to complete it within seven weeks. Edx has 2 tracks namely the verified track and the audit track which allows the students to finish off the course. During the verified track, the candidates will get unlimited but paid access to the course materials. In the audit track, the candidates will be getting limited but free access to the course materials.

Big data is the enormous amount of data that organizations have access to as a result of its scale and complexity, which makes it difficult for many analytics tools to handle or evaluate. The amount of data acquired, the frequency at which it is made available to an organization for evaluation, and the complexity or variety of that data can all be aided by tools for big data. The Google Cloud Big Data and Machine Learning Fundamentals online certification was created by Google Cloud and is taught by Google Cloud Training, which is provided through Coursera.

Google Cloud Big Data and Machine Learning Fundamentals online classes introduce the learners to the methods associated with big data and machine learning services on Google Cloud and products that enable the data-to-AI lifecycles. The Google Cloud Big Data and Machine Learning Fundamentals online course covers the steps, difficulties, and advantages of establishing a big data infrastructure and machine learning models using functionalities of Vertex AI on Google Cloud as well as the characteristics of tools like Qwiklabs, Apache Beam, AutoML, TensorFlow, BigQuery, and others.

The Preparing for the Google Cloud Professional Data Engineer Exam certification course is basically for those students and aspirants who are eligible for the Google cloud professional data engineer exam but couldn’t prepare on their own. 

The aim of this Preparing for the Google Cloud Professional Data Engineer Exam training is to help those who are eligible, have faith in their ability to take the exam and to assist those who are not qualified in developing their own training plan. The student enrolled in the course needs to go through assessments, tests, and various other assessment patterns to attain Preparing for the Google Cloud Professional Data Engineer Exam certification at the last of the completion of the course. 

The course does not have any fixed deadlines for submissions. The candidate needs to devote complete nine hours in a week to the course if he or she wants to succeed in it. The Preparing for the Google Cloud Professional Data Engineer Exam certification syllabus is entirely based on the advanced level study that gives students a 100% guarantee that they will clear this exam with good rank.  

The CS50's Introduction to Artificial Intelligence with Python Online Course is an introductory level course that aims at students who are interested in developing knowledge about artificial intelligence or AI. The course will aid students in understanding the concepts of AI and machine learning and their incorporation into Python programming.

The CS50's Introduction to Artificial Intelligence with Python Certification Course offered on the edX platform is taught over a period of 7 weeks in a self-paced manner. The course instructors are David J. Malan and Brian Yu of Harvard University, who will deliver the concepts through online course materials.

The CS50's Introduction to Artificial Intelligence with Python Training Course will acquaint students with the theoretical framework of artificial intelligence and machine learning with the help of practical demonstrations and projects. Students who complete the course successfully will receive a certificate of completion if they enrol by paying the course fee. They can also pursue it for free and access it for a limited duration. 

The need for smart analytics tools in the fields of architecture, construction, and the building industry is increasing as data sources that influence inhabitants' welfare, and the built environment's energy performance are blowing up in numbers. The Data Science for Construction, Architecture, and Engineering online course is developed to annex novel techniques and abilities to complement spreadsheets.

The Data Science for Construction, Architecture, and Engineering course centres on teaching data science skills to practitioners explicitly in the built environment industry. You will be introduced to data science while considering the background of various phases of the building life cycle. You will also gain exposure to several educational paths for a multitude of built environment-related functions.

During the time you spend learning the Data Science for Construction, Architecture, and Engineering digital course concepts, you will utilise substantial data sets from construction and design to study and apply data science methods. There are two modes to take this programme, certificate and free mode. In the free audit mode, the candidates will get access only for a limited duration. 

The delivery of various services via the Internet is referred to as cloud computing. These tools and programs comprise digital data, servers, networks, networking, and programs. Cloud-based storage enables the saving of files to remote databases as opposed to retaining them on a proprietary hard drive or local storage device. The Cloud Computing Basics (Cloud 101) certification course is developed by LearnQuest, an online learning platform, and taught by Jim Sullivan, a Master Trainer and Technology Practitioner, which is made available by Coursera.

 Cloud Computing Basics (Cloud 101) online classes incorporate 8 hours of online learning resources which begin with the fundamental concepts of cloud computing and cloud deployment and go on to describe the functionalities of storage services, cloud dynamics, and degrees of managed infrastructure. Cloud Computing Basics (Cloud 101) online training also covers a variety of subjects like HPC cloud, big data cloud, and hybrid cloud as well as discusses the concepts like bare metal computing, serverless computing, artificial intelligence, internet of things, Kubernetes, Docker, API, AWS, Azure, IBM Cloud, GCP, and salesforce.

The Introduction to TensorFlow certification course is thoroughly an online programme that is available for free for a specific period of time. The main focus of the programme is to make students aware of the Tensor flow. The training will revolve around the topics of datasets, designing and building of Tensorflow, and other features of the programme, etc. The course will take up to nineteen to twenty hours of learning.

The Introduction to TensorFlow online course is created for the students who want to learn from the course at their own pace so that they can take as much time as required to completely understand every topic. There are no last dates for the programme and it has no limitations with regards to attendance percentage or timings of attending the sessions.

The course provides an intermediate level of learning and requires no academic qualifications to get admitted into the course. Students also get an opportunity to become a certified user of the course and obtain a verified certificate when the Introduction to TensorFlow certification syllabus is completed by the participant. The language of the programme is set for English, however, participants who have a language barrier can use the subtitles that are available in Russian, Spanish, Portuguese (European), English, and French languages.

The Applications of TinyML Online Course is an open online course that discusses the applications of TinyML language and its practical applications with regard to tiny or deeply embedded devices. The course is available on the HarvardX platform with the joint effort of edX and Harvard University.

The Applications of TinyML Training Course is taught over a period of 6 weeks with the help of online course materials and informative case studies. The practical-oriented course will provide students with valuable insights into one of the most accessible and fastest-growing areas of deep learning.

The Applications of TinyML Certification Syllabus is prepared in a way its beneficial for students trying to gain a professional certificate in machine learning. The course is instructed by Vijay Janapa Reddi, Professor at Harvard University, and Laurence Moroney, Lead AI Advocate at Google. EdX gives two varied modes to take the self-paced course; verified and audit mode. The verified mode requires a course fee and the candidates will get unlimited access. In the audit mode, they can access it for a limited duration. 

In the post-pandemic era, technology adoption rates are on the rise, and businesses are experiencing its implications. If you want to design excellent user experiences to immerse your users into a new reality, Product Innovation in Emerging Technologies by Emeritus is the course for you.

The training, developed by the NYU Tandon School of Engineering, helps you catch up with the rapidly evolving environment brimming with emerging technologies. You’ll learn to apply these to digital product development and new interfaces. Besides this, the Product Innovation in Emerging Technologies certificate programme gives you a modern and historical perspective on designing experiences with emerging technologies. 

The course further offers a framework to identify opportunities, innovate with up and coming technologies at your company, and implement human-centred design approaches in ideation. Moreover, in this Product Innovation in Emerging Technologies training, you will learn via video lectures, a companion playbook, assignments, live faculty webinars, polls, discussions, video shorts, and case studies with real-world examples.

The programme spreads over six weeks. And as you finish it, you unlock a digital, verified Product Innovation in Emerging Technologies certificate.

This Data-driven Astronomy online course is designed and developed by the University of Sydney for the candidates to learn on the Coursera online education platform. This physical and astronomical course is expected to be completed by the students in twenty hours entirely. The intermediate-level course is a study about the scope of data science in the field of astronomy and the role of tools and techniques of machine learning that are used to understand the data. 

In the Data-driven Astronomy training course, the candidates are provided with the opportunity to know and comprehend the problems that may arise while handling large datasets, the strategies to use algorithms, and the ways to use the different programming languages and software tools to decipher the data. 

The course instructors for this online certification course are associate professor Tara Murphy and Simon Murphy, a postdoctoral researcher at the school of physics at the University of Sydney. 

The Data Science with Python Certification programme enables candidates to become skilled data scientists. Hence, the curriculum will teach you all the necessary concepts of Time series, statistics, and ML algorithms such as the unsupervised, supervised, and reinforcement. You will also gain fluency in other ML algorithms like clustering, regression, Random Forest, Decision Trees, Q-Learning, and Naïve Bayes. Moreover, you will experience the industry-relevant practices by solving real-time case studies on aviation, HR, social media, and healthcare.

Edureka’s Data Science with Python Certification Course offers a feature-rich curriculum. You will attend instructor-led live classes, work on frequent assignments, have a lifetime LMS access, and engage in peer interaction via the community forum. Besides, you will also receive lifetime access to the 24x7 support team to resolve technical queries.

Moreover, the online Data Science with Python Certification Course will award you with a prestigious certificate, post-completion. You will also receive a ‘resume-building tool’ to create a professional CV and ace recruitment for top-tier companies like Dell, Honeywell, Cisco, VMware, etc.

The Python with Data Science and Machine Learning certification course will help you master the core concepts of Python's programming language. It will deep dive into how Python can work on various data structures. The course will also teach the candidates how to use data to plot graphs.

The Python with Data Science and Machine Learning certification programme also gives an insight into one of the modern concepts of the digital revolution, Machine Learning. The course will cover the theoretical framework of various machine learning models and how to apply them efficiently and help to learn the core concepts in practice. 

Besides, the Python with Data Science and Machine Learning online programme by NIELIT Chandigarh is perfect to learn about the upcoming industrial trends in Data Science and Machine Learning, which will equip you with the knowledge to get better career opportunities. The course is taught by an experienced faculty and will be an immersive learning experience. 

Aspirants learn the three core concepts of Machine Learning- advanced algorithms, high-speed computation, and extracting quality data by taking up the Online Certification course in Data Science and Machine Learning. The National Institute of Electronics and Information Technology, Chennai, is providing the programme. It is aimed to develop the skills required for Machine Learning Technologies by using Python for data analysis, design visualisations, and problem-solving ML algorithms. 

The online Online Certification course in Data Science and Machine Learning classes is spread across six weeks. It will teach automation techniques for smoother transitions in everyday life across five learning modules. NIELIT’s Data Science and Machine Learning certification programme includes case studies and projects that are updated with industrial innovations. A certificate becomes available to the candidate on completion of the Online Certification course in Data Science and Machine Learning.

Mr Ripunjay Singh will be the instructor on the Data Science and Machine Learning programme by NIELIT. It requires candidates to dedicate one hour of learning on the weekdays from 5 PM to 6 PM. The Online Certification course in Data Science and Machine Learning programme is packed with mini assignments and projects with analytics, data science, python programming, statistical learning, and machine learning.

Machine Learning using R Programming certification course is a certificate course offered by NIELIT Haridwar Campus. This course is an online program that will train the candidate to be competent with the fundamentals of machine learning and the basics of R language. The programming is taught as a part of the online course and is accessible from the comfort of a laptop or computer. The course spans a duration of 6 weeks. The first four weeks focus on topics related to certification and the last two weeks are dedicated to a project. 

The project is done without adding additional see connected from the participant. The certificate is awarded upon satisfactory performance of the candidate in the final exam test and minimum attendance percentage. The course has online assignments and content presented as e-content in the form of handouts for presentations. The Machine Learning using R Programming training course will cover the basics as well as dive into practical applications in machine learning.

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The course on Machine learning using python, are apt for aspirants who want to create a promising career in the field of Machine learning. Aimed to provide insights on the fundamental concepts and techniques of Machine Learning, it is also equipped with the upgraded learning experience song with the usage of Python Language. 

The online course is offered by the National Institute of Electronics & Information Technology (NIELIT) in Haridwar, an educational intuition recognized by the Ministry of Electronics & Information Technology of the Indian government. This short course is packed with informative e-Content and is rewarded with an e-Certificate upon the successful completion of the course to each participant.

The course mainly focuses on the fundamentals in the topic of machine learning such as Data visualization, Data manipulation, Collection, details on Python, Machine learning algorithms, etc. this is also an introductory level course that provides the learners with the required knowledge in Machine learning which could even help them in molding their relevant future skills.

The Online Programme on Big Data and AI Techniques by FORE School of Management aims to explore Big Data Analytics techniques and enable learners to apply it in their research work or teaching. The programme focuses more on practice than theory, and as such, learners will have to undertake several practical assignments.

The Online Programme on Big Data and AI Techniques Training is 40 hours long and spread across six weeks. Therefore, learners will have to devote around six hours to the programme each week. Classes are live on weekdays between 2 PM and 5 PM. They can also indulge in real-time interactions with the course educators, clarifying all their doubts and queries.

For the practical exercises that are part of the Online Programme on Big Data and AI Techniques Certification Syllabus, learners need laptops with at least 4 GB RAM. The student and the teacher will work on their respective laptops and simultaneously solve each assignment. Even though it is an online programme, the learning experience is as if the teacher and the students are in a laboratory working together.

The Introduction to Data Analytics for Managers course has been gaining popularity due to the heavy reliance on data by industries worldwide. Companies have been leveraging varied data sources such as big data to a large extent to maximize the company’s performance. The course curriculum also gives a run on the different facets of machine learning. 

The Introduction to Data Analytics for Managers certification program will carry a curriculum filled with various case studies. These will give hands-on learning about how different businesses use data analytics to their advantage. Through them, you will also understand the application of data analytics in a better way. 

The Introduction to Data Analytics for Managers online program by Edx is taught by two experienced faculties members, namely Amitabh Sinha and Sanjeev Kumar. The course is best for students who want to deep dive into the web-based graphical development environment. EdX presents this course in collaboration with the University of Michigan. There are two enrolment options for joining this programme, namely, paid and free. In the free option, the candidates can access the program only for a limited duration of time. 

Automation has the potential to assist the business to maximize its worth; however, professionals must be able to understand its consequences and have the confidence to use it in their organisations and teams. The Artificial Intelligence: Implications for Business Strategy certification course teaches applicants how to incorporate machine learning (ML) and artificial intelligence (AI) into the company strategy, as well as how to create a road map for execution.

The Artificial Intelligence: Implications for Business Strategy certification by Getsmarter equips applicants with the knowledge to drive AI adoption in business, with an emphasis on the institutional implications and possibilities of robots, machine learning, and natural language processing. Candidates will be armed with the expertise required to convert their firm into a future-oriented, sustainable, and innovative enterprise.

Along with the technical features of Artificial Intelligence and Machine Learning, the Artificial Intelligence: Implications for Business Strategy online course focuses on operational and management implications of AI and ML technologies, as well as how they may be implemented in the workplace.

A Business Wire report states that 99% of Fortune 1000 firms are investing in data efforts. Big data has revolutionized and continues to revolutionize the global corporate landscape, analysts and data scientists are emerging as valuable assets inside enterprises. The Data Science Essentials online course is designed to teach students the principles of data science as well as the needs of big data analytics.

According to a Research and Markets report, The worldwide worth of the big data analytics industry is expected to be $105 billion by 2027. Working professionals and managers must now grasp the ideas and benefits of data science and utilize it to influence company choices as well as retain and recruit the appropriate personnel to drive transformation. The Data Science Essentials Training teaches the fundamentals of data science for enterprise, helping applicants to identify the value of its technology and use it to achieve success.

The Data Science Essentials syllabus supplements decision-making skills by emphasizing non-technical abilities such as data science project management and execution. This course, led by I School specialists, prepares business executives to grasp the function of data science, its potential relevance for the development of the firm, and how it may be applied in business processes.

According to a Hackernoon report, 74% of decision-makers, corporate owners and IT executives believe machine learning has the ability to transform their work and sector. Companies that use machine learning to enhance organizational performance and improve the decision-making process have clear benefits over those that do not. The Machine Learning online course aims to provide candidates with the knowledge and skills needed to comprehend the effect of machine learning and effectively articulate its integration.

It has never been simpler for businesses of all sizes to leverage the value of data. Introduction open-source and free Artificial intelligence and machine learning technologies. Embedding machine learning technologies into an organisation effectively necessitates a practical grasp of its concepts. The Machine Learning training teaches about the various types of modelling concepts used in machine learning. The Machine Learning syllabus focuses on determining the models, methodologies, and ethical implications of machine learning techniques, as well as presenting an economic case for using them in the firm.

Deep Learning with Python and PyTorch by edX is part of a two-part series on developing Deep Learning models using Pytorch. The first course in the series is titled ‘PyTorch Basics for Machine Learning’, and it covers the basics of PyTorch. Hence, you must have completed the first course to understand this programme thoroughly.

Furthermore, the Deep Learning with Python and PyTorch course syllabus aims to teach how to build deep neural networks. You will learn methods such as initialisation, dropout, batch normalisation and different types of optimisers. The programme will further explore concepts like data whitening, deep autoencoders, shallow autoencoders, autoencoder applications, etc. After you are done with all the modules, you can test your skills through the final independent project.

The Deep Learning with Python and PyTorch certification falls under the subject of Data Analysis and Statistics. This is a six-week-long intermediate-level course that will not explain things from scratch. Thus, you must have prior knowledge and interest in the field of machine learning. There are two options to join the programme, namely, verified and free audit. In the verified mode, the learners will have unlimited access to the self-paced course and in the free mode, they will have access only for a limited period. 

The Deep Learning on Azure with Python: Reinforcement Learning programme is aimed at introducing you to reinforcement learning (RL). You will use Python in Microsoft Azure to explore its relevant formal notation and various RL techniques. During this course, you will understand how RL uses Artificial Intelligence (AI) to solve complicated problems that involve numerous decisions.

During the Deep Learning on Azure with Python: Reinforcement Learning certification course, you will also discover how RL is implemented in neural networks to create more refined algorithms. Furthermore, you will study common relational algorithms like temporal difference learning and dynamic programming algorithms. The curriculum will also cover Bandits, Policy Gradient, Approximate Solution Methods, and Actor-Critic RL that Works.

The Deep Learning on Azure with Python: Reinforcement Learning training will make you skilled to implement the RL methods in Microsoft’s Azure Cognitive Services. This six-week-long online course is curated by CloudSwyft Global Systems. You also have the option to receive a course completion certificate at the end of this programme.

Fluency over data analytics is an essential skill for any organizational leader and this knowledge can be moulded into the corporate industry including making better business decisions. Business analytics: Data-driven decision making is a short certification course on harnessing these professional skills.  

The online course is offered by Emeritus in association with Rotman school of management who designed this executive program. Instructed by the experienced faculty of Rotman School of Management, the course encapsulates fundamental topics and applications usage of data analytics with innovative learning methods. 

Each module is designed to help the learner craft the narrative for their company’s enhanced data literacy. The course mainly focuses on understanding the applications of data which involves examining tools and techniques of data and analytics in a real-world setting. It helps the learner to fine-tune their fluency with data concepts, challenges, and applications which could build an effective and data-driven business organization.

Machine Learning for Accounting with Python is an intermediate-level certification course offered by the University of Illinois at Urbana-Champaign. The online course can be covered by the learners within about 6 weeks. Machine Learning for Accounting with Python Certification Syllabus will walk you through the application of machine learning algorithms in problems related to accounting. 

Learning for Accounting with Python Certification Course, offered by Coursera, is the third in the four courses in the Accounting Data Analytics Specialization. Through the online course, the learners will be able to understand classification, clustering, Python programming, machine learning and the like. Machine Learning for Accounting with Python Certification by Coursera is an online programme prepared in a way that enables the students to take the course at their convenience and time. 

The ‘Text Analytics 1: Introduction to Natural Language Processing’ online course is an overview of the strategies involved in Natural Language Processing(NLP) and the various aspects of computational linguistics. This course enables students to get hands-on experience with NLP and the process of performing analysis in Python with regard to the creation of pipelines.

Edx provides this course in association with the University of Canterbury(UC) for a period of six weeks and the students are required to spend at least three to six hours per week to complete the course successfully. This computer science course is self-paced and the learners in this program are led by the instructors from UC, Jonathan Dunn(Lecturer), Tom Coupe(Associate Professor), Jeanette King(Professor), and Girish Prayag(Professor).

In the ‘Text Analytics 1: Introduction to Natural Language Processing’ online training program, students will engage themselves with concepts of text processing, text mining, sentiment analysis, and topic modelling. The participants will receive a certificate after finishing the course of study and the graded assessments. The self-paced programme can be taken free of cost and has a limited duration. They can also upgrade it to the verified mode by paying for the course and getting unlimited access to the course materials. 

The ‘Text Analytics 2: Visualizing Natural Language Processing’ online course is developed for the students to gain knowledge and expertise with the visualization and interpretation of outputs in text analytics along with the scientific overview of understanding language computations.

This computer science course is provided by the Edx educational platform in collaboration with the University of Canterbury for the classes and modules. This online program is scheduled for a period of approximately six weeks and the candidates are expected to spend a minimum of three to six hours per week to finish the course modules.

The ‘Text Analytics 2: Visualizing Natural Language Processing’ is a self-paced learning program and the students can study independently with the curriculum instructed by faculty from the University of Canterbury such as Jonathan Dunn (Lecturer), Jeanette King (Professor), Tom Coupe (Associate Professor), and Girish Prayag (Professor). The participants will receive a certificate that can be shared online for the benefit of career advancement if they choose the verified mode by paying the course fee. They can also join the self-paced programme free of cost and get limited access to the programme. 

The primary focus of the GCP Certification Training course is to prepare you for the Google Cloud Platform Training. Through the certification programme, you will gain an understanding of the core principles and fundamental concepts of the Google Cloud Platform. 

Further in the course, you will learn how to manage Google Cloud Platform (GCP) services, including Google Cloud Platform’s database, networking, and security services, among others. The Google Cloud Certification Training- Cloud Architect syllabus will cover the basics of cloud computing and the core infrastructure of Google Cloud Platform. The course curriculum is strictly in accordance with the exam guide officially provided by Google.

Moreover, the GCP Certification Training course by  Edureka also focuses on how to use the major command-line tools for importing data in Google Cloud Storage and how to run queries for data analysis. You will become skilful at creating a migration plan, designing strategy, and collecting and analysing metrics.

The Machine Learning and AL Bootcamp by Jigsaw Academy is the one-stop solution to acquiring in-depth knowledge about the core concepts of machine learning and artificial learning. The curriculum broadly covers topics such as machine learning (ML) techniques, deep learning (DL) techniques, their algorithms, the mathematics behind such algorithms, deploying such ML and DL algorithms for problem-solving and so forth. 

Moreover, the Machine Learning and AL Bootcamp course will also help you to receive first-hand access to knowledge and insights from industry experts. You will be able to learn and master machine learning from the best minds. 

Also, the course provides a comprehensive learning experience, where you will become adept at applying machine and deep learning techniques effectively.

Furthermore, throughout the Machine Learning and AL Bootcamp, you will learn to apply such techniques to both unstructured and structured data via real-time case studies. You will also understand how to implement machine learning for business applications. 

The Machine Learning with Python certification course offered by IBM is a comprehensive program designed to introduce learners to the basics of machine learning using the Python programming language. Machine Learning with Python programme offered by IBM is the 13 hours (approx.) duration certification course having 6 moudules in total where students can learn on their own pace.

The Machine Learning with Python  certification course, offered by IBM via Coursera, is the intermediate level programme where students will learn classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and Logistic Regression. You’ll also learn about the importance and different types of clustering such as k-means, hierarchical clustering, and DBSCAN.  Machine Learning with Python certification course offered by IBM helps the students to learn new concepts from industry experts and develop job-relevant skills with hands-on projects along with shareable career certificate from IBM.