Free It Software Courses & Certifications

Amazon Web Services (AWS), the most comprehensive and vastly adopted cloud platform across the globe, is a fast, easy and cost-efficient platform to build ML applications. The AWS Machine Learning offers tools and services which cater for the developers and organisations to build ML models more efficiently. Globally, AWS Machine Learning is used by developers to build ML models that can test product designs, assess property damages, improve healthcare operations, analyse customer behaviour, fraud detection and much more.

Getting Started with AWS Machine Learning certification course is an online offered by AWS through the Coursera platform. This certificate programme will assist the participants to gain familiarity and working knowledge of AWS Machine Learning. The course content spreads over 5 weeks and includes module videos covering almost every significant aspect of machine learning. Participants will receive a shareable certificate upon completion of this online certificate programme.

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. 

The certificate course called Securing Digital Democracy by Coursera prepares every citizen about the true potential of electronic and internet voting aspects in the future. It teaches you everything that you must know about the true risks and security issues in our times. This course takes a look at the different times of past, the present, and future aspects of conducting elections and the various technologies involved in elections. This course will teach candidates about exploring the different subsets intersected by the factors involved in the process like Including the use of computers, human factors, Cybersecurity and its threats, public policy, and other related factors.

This course is rightly titled securing digital democracy since it deals with the most important aspect of democracy, the elections. The course teaches in detail the entire electoral process and the challenges one can encounter and hence prepare for in the future course of elections. With insights from the past with a detailed history of voting, this course is curated with a very structured format that is easy to grasp and allows an understanding of every candidate from different backgrounds. For candidates from public policy, cybersecurity, and software testing this course will develop an understanding of the electoral process and its changing dynamics that will better help them develop tools for the elections of the future.

The Deep Learning Essentials program by edX will help candidates discover the issues of discrimination and bias in Machine Learning and gain valuable insights regarding the subject. They will become adept at performing tasks like signal processing, computer vision, robotics, sequential decision-making, and natural language processing.

Besides, the University of Montreal offers the Deep Learning Essentials training which is designed by IVADO, a hub of scientific and economic data science and Mila. The scientific director of this course is Yoshua Bengio, a reputed expert in artificial intelligence and a pioneer in Deep Learning, who is also a professor at the University of Montreal.

Rife with video tutorials, tests, and assignments, the Deep Learning Essentials certification course also provides diverse learning tools to help candidates become adept in deep learning's fundamental concepts and methods. 

On successful course completion, candidates can also secure a verified certificate from edX to acknowledge their newly acquired knowledge in the field. The candidates may choose from any one of the tracks available namely verified and audit to complete the programme. Both the tracks are self-paced but during the audit track, the candidates shall receive limited period access to the course. On the other hand, the verified track will offer unlimited time for accessing the course.

The Applied Deep Learning Capstone Project certification programme is a five-week-long online course curated by IBM. During this capstone project, you will get practical, hands-on experience in developing, training and testing a Deep Learning model. For this purpose, you will be using either PyTorch or Keras.

edX’s Applied Deep Learning Capstone Project is an advanced-level programme that is also a part of a Deep Learning professional certificate of edX. With the help of this course, you will learn how to preprocess and load data for a real-life problem, create a model and finally validate it. 

The Applied Deep Learning Capstone Project programme by edX requires only two to four hours per week to study. You will learn through video lessons and ultimately master the procedure of generating a Deep Learning pipeline. At last, you are required to present a project report to showcase your competence in the domain of Deep Learning. EdX provides two tracks to pursue the self-paced course; verified and free audit. In the former mode, the learners can access the programme unlimited and get a certificate of completion. In the free mode, they can audit it for a limited duration. 

Training sophisticated Deep Learning models takes plenty of time. The Using GPUs to Scale and Speed-up Deep Learning certification programme sheds light on how accelerated hardware like Nvidia GPU (Graphics Processing Unit) or Google’s TPU (Tensor Processing Unit) can be used to shorten computations time on the cloud.

During edX’s Using GPUs to Scale and Speed-up Deep Learning course, you will understand what accelerated GPU-based hardware is and how it can help you overcome scalability challenges in Deep Learning. You will also get familiar with IBM’s Power Systems with Power AI and Nvidia GPU.

The Using GPUs to Scale and Speed-up Deep Learning will also acquaint you with popular Machine Learning dependencies and learnings supported by Power AI. These include Caffe, Theano, Tensorflow and Torch. Lastly, with this course, you will get practical experience of deploying Deep Learning networks on accelerated hardware for numerous problems, such as classifying videos and images.

The Deep Learning Fundamentals with Keras online course by edX is designed to familiarise you with the domain of Deep Learning. It is a five-week-long programme, during which you will learn about the basics of various Deep Learning models, the fundamentals of neural networks, and some of the most interesting Deep Learning applications.

Through the Deep Learning Fundamentals with Keras certification course, you will get practical experience, building a Deep Learning model with the powerful and easy-to-use Keras library. Also, you will develop an understanding of unsupervised and supervised Deep Learning models.

The Deep Learning Fundamentals with Keras certification syllabus is divided into four extensive modules. You are required to devote merely two to four hours every week to your studies.  As you progress across the modules, you acquire in-depth knowledge of how Keras is used to train, test and build Deep Learning models. Moreover, you will understand how neural networks learn. Upon completion, you can also get the verified certificate and earn a skill badge to showcase your acquired knowledge if you pursue it by paying free. For free, you can get a limited duration of access to the course. 

Container technology is a packaging method that enables applications to run with isolated dependencies and has existed for years. The most popular options in container technologies are Kubernetes and Docker, both with distinct features and challenging to orchestrate. Building Containerized Applications on AWS Online Certification by Edx is an introduction to the use of container technologies in modern applications, helping you solve such problems. 

Furthermore, the Building Containerized Applications on AWS certification syllabus explores various services such as Amazon Elastic Kubernetes Service, Amazon Elastic Container Service, and Amazon Elastic Container Registry. 

Through the  Building Containerized Applications on AWS training, students will gain exposure to the services mentioned above, with thorough guidance from expert instructors. The certification program curriculum also includes practical assignments and lab exercises to help students learn about managing container technologies.

Besides, the Building Containerized Applications on AWS program is a free online course that gives students an opportunity to learn new skills and earn a digital certificate to add to their CV.

This course by edX has been designed keeping in mind the challenges faced while dealing with data lakes. It can be attributed to the quantum of data and its growth over time. Thus, judicious steps need to be employed to avoid prevalent mistakes. With this aspect serving as a foundation stone, this program will address key challenges.

To begin with, the founding principles of Data Lakes are introduced followed by the organization of the data, which subsequently leads to its refining. The teachings of this program are targeted at professionals such as IT Administrators and Architects who need to design and maintain Data Lakes for a sustainable and scalable future. 

It’s a 5-week programme that seeks student input of 1 to 4 hours per week. This intermediate-level course is presented in English and has the advantage of being self-paced. Thus, working professionals can decide on their choice of learning hours. 1 to 3 years of experience as a Software Engineer is a must. 

This particular course on edX has 2 tracks namely audit and verified both of which is enrolled for shall be completed in may be opted for by a candidate for enrolling. Both the tracks have an instructor-led mode but the audit track offers only limited access to the course materials without any cost and provides no certificate of completion. The verified track offers unlimited access and also offers certification of completion only if the candidates are interested in paying a fee.

The Analyzing Data with Excel certification course is a self-paced 5 weeks online programme that is designed and offered by IBM on the platform of edX. By just focusing on 3-5 hours every week at their own speed, the learners can finish learning. Though the course is initially free, a nominal fee is required in case students wish to upgrade, get unlimited material access, and receive certificates along with verified badges. This is an introductory course that gives applied knowledge, and hands-on practice of lab exercises.

Analyzing Data with Excel training will give knowledge in the in-demand topics required for business. The students will be able to build basic knowledge of different kinds of Excel spreadsheets for performing the fundamental data analysis. This online introductory programme with zero admission prerequisites actually in its syllabus covers the working features of Microsoft Excel that will assist students in analysing their data.

The candidates can select from among the 2 tracks, the audit track and the other, the verified track. If one wants limited but free access their pick can be the audit track and if someone needs unlimited course material access they can upgrade to the paid verified track.

After virtualisation, cloud-native and containers are one of the most significant finds of the ITC industry. Several organisations are transitioning to this platform to gain competitive advantage. So, pursuing the Introduction to Containers, Kubernetes and OpenShift certification course will help you leverage this opportunity for personal gains. It is an introductory-level programme for six weeks.

The introduction to containers kubernetes and openshift docker introduction has a self-directed training model. It will allow you to learn at your speed and enhance your employability quotient. After completing this course, you will develop and deploy cloud-native applications effectively. You will understand the difference between containers and virtual machines through the computer science course curriculum.

Furthermore, the Introduction to Containers, Kubernetes and OpenShift training will enable you to take on advanced roles in your organisation. It is also a beneficial programme for an individual who wants to become a cloud practitioner. The course dives into the concepts of how and why containers are important in cloud computing.

Machine Learning (ML) is rapidly transforming the world. The Big Data Applications: Machine Learning at Scale certification programme is an advanced-level online course to provide you with comprehensive ML knowledge. During the course, you will explore what type of real-life problems can be solved with ML.

Offered by Yandex, the Big Data Applications: Machine Learning at Scale training by Coursera will equip you with skills to build ML models through practical assignments. You will also learn how to create your recommender system.

Throughout the Big Data Applications online training’s five-week duration, you will go through extensive reading material, practise exercises and quizzes. It will also include exclusive video lessons delivered by top-rated instructors.

Coursera’s Big Data Applications online course will educate you on the various applications of Big Data and ML. The skills you develop will enable you to undertake different kinds of pragmatic machine learning tasks. Upon course completion, you can also earn the coveted e-certificate, which is purchasable.

Data Science Math Skills certification is a 13 hours online course that is divided into 5 weeks and is an offering of Coursera along with Duke University. This course is very useful for those who want to keep on learning the basics of mathematics irrespective of whether they have learnt pre-calculus or algebra. Learning math skills through both androids, and apple devices will create the basis for successful data science.

Data Science Math Skills training forms the introduction for core math skills that data science requires, without any extra complexity, by introducing math symbols, and unfamiliar ideas one at a time. Besides this being a beginner course, this certification can act as a prerequisite for the “Mastering Data Analysis in Excel” course. Anyone who has successfully completed this gets to understand advanced concepts of maths like problem-solving along with certificates that are shareable.

Haptic devices are mechanical devices that let the users feel, touch, and control objects in remote or virtual environments. The Introduction to Haptics certification course aims to teach you about haptic technology in detail. You will develop a sense of awareness about the abilities and weaknesses of the human touch, along with learning how to build these mechatronic devices.

Through the learnings of the Introduction to Haptics online programme, you will acquire pragmatic cross-disciplinary engineering skills connected to mechanical engineering, bioengineering, robotics, computer science, and electrical engineering. This course developed by Stanford Online will help you comprehend the linkage between equations that explain physical interplay and how they feel.

The Introduction to Haptics training also offers online quizzes to test your understanding of the concepts. You also have the option to participate in laboratory assignments by using/building a ‘Hapkit.’ This practical approach will give you hands-on experience in testing haptic projects, making circuits, and putting mechanical systems together. 

Edx offers 2 varied tracks which can be used to opt into the course and then they shall be given access either for a limited period of time or the access offered may be unlimited. In the case where the students want unlimited access, they will have to choose the verified track and where they want limited access for free they will have to select the audit track.

A 5-weeks online programme, the Hurricane Tracking with Satellite Data course is developed to impart students with comprehensive knowledge about how they can analyse satellite data related to hurricanes and predict hurricanes’ paths to minimise the damage caused by them. 

Satellite-enabled data allows us to monitor, track and observe hurricanes from a secure distance. You will be gaining insights on how these datasets can be explored to derive descriptive stats. With the help of Hurricane Tracking with Satellite Data online programme, you will understand the important ideas of data science imperative to analyse, process, and finally interpret the large sets of data. 

Utilizing the tracking data made possible by satellites, you will see how predicting the paths of hurricanes is crucial in administrating, evacuations, and relief efforts to save countless lives that are endangered by these natural disasters.

The Hurricane Tracking with Satellite Data course by FutureLearn uses practical case studies and tutorials for enabling you to extract vital information from the satellite datasets.

The Fundamentals of TinyML Training Course is an open course provided on the HarvardX platform coordinated by edX and Harvard University. The course will introduce students to the fundamentals of embedded systems and machine learning along with the core aspects of TinyML language.

The Fundamentals of TinyML Certification Syllabus will benefit students who are interested in data analysis and statistics. The course is an introductory level course that requires students to have knowledge about basic scripting techniques in Python. The course is supported by online study materials and instructed by Vijay Janapa Reddi and Laurence Moroney.

The Fundamentals of TinyML Course is taught over 5 weeks in a self-paced manner. The course focuses on the main aspects of deep learning, machine learning, and embedded devices and systems, like smartphones and other devices. Upon the successful completion of the online exams and assignments, students will receive a certificate if they choose the verified mode with the course fee. In the free mode, they can audit it for a limited period. 

A considerable amount of the world’s data is unstructured, including text, sound, images, etc. By joining the Deep Learning with TensorFlow certification course, you will learn how Deep Learning can be applied with TensorFlow to this kind of data and solve real-life problems. You will study the main functions, execution pipeline, basic concepts and operations of TensorFlow.

During the 5-week duration of the Deep Learning with TensorFlow online program, you will explore various kinds of Deep Architectures, like Autoencoders, Recurrent Networks, and Convolutional Networks. Also, you will learn how to implement TensorFlow for backpropagation to adjust the biases and weights while training the neural networks.

With the help of edX’s Deep Learning with TensorFlow course, you will learn how TensorFlow can be used in regression, minimizing error functions, curve fitting and classification. The course offers you free access to its contents for a limited duration and you can also get the option to avail of a professional certificate on completion after paying the prescribed fee. 

This fundamental course focuses on the mathematical approach to networks and optimization issues. This course is presented by edX, a popular online education medium along with the institution of Ecole Polytechnique Federale de Lausanne (EPFL), a top European institution for technology and science. This short intermediate course is provided with a flexible learning system and a comprehensive curriculum which will be under the experienced EPFL professor, Michel Bierlaire. The students can either go for a free audit session with limited benefits or a verified track session with complete Optimization: Principles and algorithms- Network and discrete optimization certification benefits.

The course mainly highlights five different sections: Transhipment, Discrete optimization, Shortest path, Exact methods for discrete optimization, and Networks which will be individually assessed and graded as well. Apart from these key concepts, the syllabus focuses on other important aspects such as modelling, the curse of dimensionality, total unimodularity, network representations, and so on. Two different tracks are available on edX which may be opted for by the students to complete the course. Both the tracks are self-paced but during the verified track, the candidates may access the course for a lifetime by paying some fee. To access the audit track, nothing is charged but the materials will only be accessible for a limited period.