6 Best Blockchain Courses

We came up with a selection of the 6 best Blockchain courses. There is a mix of free and paid courses or programs from different platforms. The list below will be updated regularly with the most trending and popular Blockchain courses.

Princeton University logoTo really understand what is special about Bitcoin, we need to understand how it works at a technical level. This course will teach you everything you need to be able to separate fact from fiction when reading claims about Bitcoin and other cryptocurrencies. You will have the conceptual foundations you need to engineer secure software that interacts with the Bitcoin network. You will also be able to integrate ideas from Bitcoin in your own projects.

Course highlights:

  • 100% Online Self-Paced
  • Duration: 23 hours to complete
  • Does not offer certificate upon completion
  • Skills: Bitcoin Network, Blockchains, Cryptocurrency, Bitcoin

Blockchain Developer NanodegreeDemand for blockchain developers is skyrocketing. In this brand new nanodegree program from Udacity you will learn the fundamentals of the blockchain platform. You will create your own private blockchain, and secure a digital asset using blockchain identity. You will also explore the Ethereum platform, and use Solidity and smart contracts to develop your own decentralized app. Prior to taking this program, trainees should be comfortable with object-oriented programming, and developing web apps in Javascript.

Nanodegree highlights:

  • Includes 5 courses
  • Duration: 4 months
  • Effort: 10 hrs / week
  • Skills: Ethereum Blockchain, Blockchain Architecture, Data Auditing

Berkeley logoThis edX course is offered by the University of California, Berkeley. It covers many key topics in the blockchain space. First, it takes a look at distributed systems and alternative consensus mechanisms, as well as cryptoeconomic and proof-of-stake, the fundamental applications of bitcoin and blockchain technology, the challenges and solutions around scaling blockchain adoption, and the measures that the government is taking to regulate and control blockchain technology. The course wraps up by taking a look at the various blockchain ventures today and conclude with a blockchain-based future thought experiment. This is the second course in the Blockchain Fundamentals Professional Certificate program.

Course highlights:

  • Online Self-Paced 
  • Duration: 6 weeks
  • Effort: 3-5 hrs / week

Hyperledger Fabric AdministrationThis course is designed for system administrators who want to take deeper dive into how to manage, implement and operate on a daily basis within the Hyperledger Fabric network. Learners will get a good understanding of the Hyperledger Fabric network topology, handle chaincode operations such as making chaincode packages accessible to peers, invoking and interacting with the chaincode logic from the CLI, as well as administer identities, provide permissions, and revoke or remove malicious nodes from the network. You will also troubleshoot network components by learning how and where to configure component logging, and learn about service discovery and private data. 

Course highlights:

  • 100% Online Self-Paced 
  • Includes 6 chapters
  • 18-20 hours of course material

The Linux Foundation logoThe Hyperledger Sawtooth for Application Developers edX course starts with the basics of blockchain technology and the concepts of permissioned networks, then describes the important features of Hyperledger Sawtooth. It includes a sample distributed application, Sawtooth Simple Supply, that is based on a simplified supply chain example. This blockchain application includes a web-app frontend, a transaction processor (the equivalent of a smart contract) for the blockchain business logic, and a custom REST API for communication. Learning how to code this sample application will teach you about important Hyperledger Sawtooth concepts and will help you understand how to create your own enterprise-level Hyperledger Sawtooth application. This course requires programming experience with Python and JavaScript.

Course highlights:

  • Online Self-Paced 
  • Duration: 14 weeks
  • Effort: 1-2 hrs /week
Advance your skills in the blockchain learning pathDemand for Blockchain skills has skyrocketed as companies in virtually all industries around the world rush to ensure they’re not missing opportunities or being outflanked by competitors adopting this digital, decentralized trust technology to their own needs. For those in the IT industry especially, a thorough understanding of how Blockchain works, and what the key development skills are, can set you on a new career development path. In this LinkedIn Learning Path, you will master fundamental blockchain and cryptocurrency concepts, learn the development competency skills for Solidity and Ethereum and also master blockchain programming for iOS.
 

Learning Path highlights:

  • Online Self-Paced 
  • Includes 7 courses
  • Duration: 9 hrs 4 min
  • Skills: Blockchain

10 Best Cloud Computing Courses

This is a selection of the 10 best Cloud Computing courses across several e-learning platforms. Depending on the platform, some courses are free and give you the option to earn a verified certificate after being completed, and others require a one-time purchase or a monthly subscription. The list below will be updated regularly with the most trending and popular Cloud Computing courses.

Cloud Computing

Google Cloud logoThe Coursera course Site Reliability Engineering: Measuring and Managing Reliability offered by Google Cloud, teaches the theory of Service Level Objectives (SLOs), a principled way of describing and measuring the desired reliability of a service. This course will allow learners to apply these principles to develop the first SLOs for services they are familiar with in their own organizations. You will also learn how to use Service Level Indicators (SLIs) to quantify reliability and Error Budgets to drive business decisions around engineering for greater reliability. In a nutshell, the trainee will understand the components of a meaningful SLI and walk through the process of developing SLIs and SLOs for an example service.

Course highlights:

  • 100% Online Self-Paced
  • Duration:  13 hours to complete
  • Skills: SRE (Site Reliability Engineering), SLOs (Service Level Objectives), SLI (Service Level Indicators)

The Linux Foundation logoThis edX introductory course, taught by cloud experts from The Linux Foundation, will help you grasp the basics of cloud computing and comprehend the terminology, tools and technologies associated with today’s top cloud platforms. Understanding cloud technologies tops the list of most important skills for any developer, system administrator or network computing professional seeking a lucrative career in technology. This course gives you a primer on cloud computing and the use of open source software to maximize development and operations. Topics covered include: next-generation cloud technologies (Docker, Cloud Foundry, Kubernetes and OpenStack); scalable and performant compute, storage and network solutions (SDN and SDS); and solutions employed by companies to meet their business demands (DevOps and CI/CD). No previous cloud experience is required for this course.

Course highlights:

  • Online Self-Paced 
  • Duration: 14 weeks
  • Effort: 3-4 hrs /week

Google Cloud logoThe Architecting with Google Kubernetes Engine Specialization will teach you how to implement solutions using Google Kubernetes Engine (GKE), including building, scheduling, load balancing, and monitoring workloads, as well as providing for discovery of services, managing role-based access control and security, and providing persistent storage to these applications. This specialization starts with the GCP core infrastructure fundamentals and then deep dives into architecting with the GKE. The course also incorporates hands-on labs using the Qwiklabs platform.

Specialization highlights:

  • 100% Online Self-Paced
  • Includes 4 courses
  • Duration: 1 month to complete
  • Effort: 15 hrs / week
  • Skills: Google Compute Engine, Google App Engine (GAE), Google Cloud Platform, Cloud Computing
Prepare for Microsoft Azure Administrator Certification (AZ-103)Microsoft Azure is one of the leading enterprise-grade cloud computing platforms. This LinkedIn Learning path provides IT professionals who have existing knowledge of Azure infrastructure with the skills they need to prepare for the Microsoft Azure Administrator certification exam (AZ-103). In a nutshell, you will learn: how to create, deploy, and maintain virtual machines; how to manage identities securely in Azure AD; and explore the domains and requirements of the AZ-103 exam. 
 

Learning Path highlights:

  • Online Self-Paced 
  • Includes  8 courses
  • Duration: 12 hrs  32 min
  • Skills: Cloud Administration, Cloud Computing

Google Cloud logoThe Google Cloud Professional Cloud Architect certification was ranked one of the top paying IT certifications of 2019 by Global Knowledge. This program provides the skills you need to advance your career as a professional cloud architect and prepares you for success on the industry-recognized Google Cloud Professional Cloud Architect certification. You will be deploying solution elements, including infrastructure components such as networks, systems and applications services, and you will also gain great real world experience through a number of hands-on Qwiklabs projects.

Professional Certificate highlights:

  • 100% Online Self-Paced
  • Includes  6 courses
  • Duration: 3 months to complete
  • Effort:  5 hrs / week
  • Skills: Google Compute Engine, Google App Engine (GAE), Google Cloud Platform, Cloud Computing, Virtual Machine, Network Architecture, Debugging, Cloud Storage, Data Store, Load Balancing, Virtual Private Network (VPN), Autoscaling

USMx logoIn this Cloud Computing MicroMasters® program, you will learn about Infrastructure As A Service (IaaS), Platform As A Service (PaaS), Software As A Service (SaaS), and other “X as a service” platforms. You will receive key foundational knowledge about legal and compliance issues, security and risk mitigation and how to follow industry standards and best practices. You will also gain hands-on experience in implementing, configuring and managing cloud technologies. IT professionals not already working with cloud technologies will gain a solid foundation while those with some cloud experience will gain a more in-depth understanding of other cloud technologies and other knowledge such as security, policy, and legal and compliance issues. Students who enroll and verify in this Cloud Computing MicroMasters program can earn up to $675 in AWS promotional credits!

MicroMasters highlights:

  • 100% Online Instructor-led (with due dates for assignments and exams)
  • Includes 4 graduate-level courses 
  • Duration: 8 months
  • Effort: 8-10 hrs / week
  • Skills: Cloud Computing

Intro to Cloud ComputingIn this Udacity course, you will learn foundational cloud computing skills that will set you on your path to a career in cloud computing. First you will learn about fundamental concepts such as the advantages of cloud computing, deployment models, and the similarities and differences across major cloud service providers. After having learned the fundamentals, you will gain valuable hands-on practice using AWS to create identity and access management policies, store data in an S3 storage bucket, and launch an ec2 instance and set up automated provisioning. Last but not least, you will be introduced to serverless architecture and data storage using AWS Elasticache. This free course serves as a good preparation for the Cloud Developer Nanodegree.

Course highlights:

  • Online Self-Paced 
  • Duration: 2 months
  • Skills: Cloud Computing, AWS Console, Compute Services, Serverless Architecture, Cloud Databases

Prepare for the CompTIA Cloud+ (CV0-002) CertificationThis LinkedIn Learning path provides system administrators a comprehensive method for studying the skills required to successfully prepare for the latest CompTIA Cloud+ exam. It includes in-depth courses teaching the skills and abilities related to each exam domain, and provides insights into resources you can use to prepare and register for the exam. It also covers requirements around continuing education and certification renewal. In a nutshell, you will: learn testing, storage, and troubleshooting techniques related to configuration and deployment; explore the technologies related to effective security practices; and develop essential skills related to automation, BCDR, and metrics for management and reporting.

Learning Path highlights:

  • Online Self-Paced 
  • Includes  3 courses
  • Duration: 10 hrs 14 min
  • Skills: Security, Cloud Computing

Cloud Developer NanodegreeIn the Cloud Developer Nanodegree from Udacity you will start by learning the fundamentals of cloud development and deployment with AWS. Then, you will move into building different apps leveraging microservices, Kubernetes clusters, and serverless application technology. Prior to taking this program, trainees should be comfortable with object-oriented programming, and developing web apps in Javascript. There are more than 50K Cloud Computing jobs in the US alone, being Cloud Developer one of the most in-demand roles.

Nanodegree highlights:

  • Includes 4 courses
  • Duration: 4 months
  • Effort: 10 hrs / week
  • Skills: AWS, Microservices, Serverless Architecture, Kubernetes

Cloud Foundry for Developers LFD232This The Linux Foundation course is designed to equip developers with a valuable, marketable skill set across all Cloud Foundry certified platform distributions. You will learn how to use Cloud Foundry to build, deploy and manage a cloud native microservice solution. The course has extensive labs so developers can learn by doing. Some of the areas it focuses on, are: Cloud Foundry architecture; Applications and Services; Cloud Native design; and Troubleshooting & Debugging. Some prerequisites include: being an active developer, comfortable using command line tools and familiar with basic cloud computing concepts. Familiarity with Java/Spring, Node.js and/or Ruby is a plus.

Course highlights:

  • 100% Online Self-Paced 
  • Includes 22 chapters
  • 40-50 hours of course material

7 Best Cybersecurity Courses

This is a selection of the 7 best Cybersecurity courses across several e-learning platforms. Depending on the platform, some courses are free and give you the option to earn a verified certificate after being completed, and others require a one-time purchase or a monthly subscription. The list below will be updated regularly with the most popular courses in Cybersecurity.

Cybersecurity courses

Google logoThis Coursera course covers a wide variety of IT security concepts, tools, and best practices. It introduces threats and attacks and the many ways they can show up. The course will teach some background of encryption algorithms and how they are used to safeguard data. Then, it deep dives into the three As of information security: authentication, authorization, and accounting. It also covers network security solutions, ranging from firewalls to Wifi encryption options. The course is rounded out by putting all these elements together into a multi-layered, in-depth security architecture, followed by recommendations on how to integrate a culture of security into your organization or team.

Course highlights:

  • 100% Online Self-Paced
  • Duration:  29 hours to complete
  • Skills: IT Security, Criptology, Network Security
Become a CompTIA Security+ Certified Security ProfessionalThe CompTIA Security+ certification is the leading entry-level IT certification for those looking to break into the exciting field of Cybersecurity. This LinkedIn Learning path maps to the 6 domains that make up the SY0-501 exam objectives. Get the necessary skills to become certified, from identifying and mitigating risk and providing infrastructure security to troubleshooting security incidents. In a nutshell, you will: learn basic IT security concepts and best practices; identify security threats and learn how to defend against them; and prepare for and pass the CompTIA Security+ (SY0-501) exam.


Learning Path highlights:

  • Online Self-Paced 
  • Includes 7 courses
  • Duration: 21 hrs 8 min
  • Skills: Network Security, Cryptography

IBM logoA growing number of exciting, well-paying jobs in today’s security industry do not require a college degree. This Coursera 8-course Professional Certificate will give you the technical skills to become job-ready for a Cybersecurity Analyst role. Instructional content and labs will introduce you to concepts including: Network Security, Endpoint Protection, Incident Response, Threat Intelligence, Penetration Testing, and Vulnerability Assessment. The program applies concepts through industry tool virtual labs and wraps up with a real-world security breach hands-on project and to provide you with the confidence to start a career in Cybersecurity.

Professional Certificate highlights:

  • 100% Online Self-Paced
  • Includes 8 courses
  • Duration: 8 months to complete
  • Effort: 4 hrs / week
  • Skills: Information Security Analyst, IT Ssecurity Analyst, Security Analyst, Junior Cybersecurity Analyst, Information Security (INFOSEC), IBM New Collar, Malware, Cybersecurity, Cyber Attacks, Database vulnerabilities, Network Security, SQL Injection

University of Washington logoThis edX course, offered by the University of Washington, is an introduction to the exciting field of Cybersecurity. As our daily lives become more and more dependent on Internet-based tools and services, and as those platforms accumulate more of our most sensitive data, the demand grows for experts in Cybersecurity. In this course, you will gain an overview of the Cybersecurity landscape as well as American and International perspectives on the field. This course will also cover the legal environment that impacts Cybersecurity as well as predominant threat actors.

Course highlights:

  • 100% Online Self-Paced
  • Duration: 6 weeks
  • Effort: 2-5 hrs / week
  • Skills: Cybersecurity

Introduction to Cybersecurity NanodegreeThe Introduction to Cybersecurity Nanodegree program will allow you to start a career in Cybersecurity and learn the skills required to become a security professional. In this program, you will learn how to evaluate, maintain, and monitor the security of computer systems. You will also learn how to assess threats, respond to incidents, and implement security controls to reduce risk and meet security compliance goals. This program requires to have previous knowledge in Network connectivity and OS fundamentals.

Nanodegree highlights:

  • Includes 4 courses
  • Duration: 4 months
  • Effort: 10 hrs / week
  • Skills: Threat Assessment, Security Vulnerabilities, Compliance, Governance, Risk, Incident Response

Become an IT Security SpecialistLearn the core concepts needed to secure your organization’s network as an IT security specialist. In this LinkedIn Learning path, you will cover all the foundations of IT security: from practical skills for securing hardware and network data to the basics of cryptography and cybercrime investigation and response. In a nutshell, you will: learn the principles of IT security and Cybersecurity; develop practical skills for securing networks; and investigate cybercrimes and know the basics of computer forensics.

Learning Path highlights:

  • Online Self-Paced 
  • Includes 11 courses
  • Duration: 19 hrs 3 min
  • Skills: Information Security, Network Security

CompTIA CySA+ (CS0-001/002) Complete Course & Practice ExamThis Udemy course provides everything a learner needs in order to study for the CompTIA Cybersecurity Analyst+ (CySA+) (CS0-001/CS0-002) certification exam. It includes downloadable study guide, quizzes to check your knowledge as you progress through the videos, and a full-length practice exam to test your knowledge before test day. Taught by an expert in IT and Cybersecurity with 20+ years of experience, this course will prepare you to pass the certification exam and/or to serve on your organization’s cyber defense team. It covers all the following topics: Threat Management; Vulnerability Management; Cyber Incident Response; Security Architecture and Tool Sets; Threat and Vulnerability Management; Software and Systems Security; Security Operations and Monitoring; Incident Response; and Compliance and Assessment.


Course highlights:

  • Online Self-Paced 
  • 17.5 hours on-demand video
  • Full lifetime access
  • Skills: Information Security, Network Security

8 Best Data Science Courses

We came up with a selection of the 8 best Data Science courses across several e-learning platforms. Depending on the platform, some courses/programs require either a one-time purchase or a monthly subscription. The list below will be updated regularly with the most popular courses in Data Science.

Michigan University logoThis five-course specialization offered by the University of Michigan, introduce learners to Data Science by using Python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. This is one of the most popular Data Science Specializations out there. 

Specialization highlights:

  • 100% Online Self-Paced
  • Includes 5 courses
  • Duration: 5 months to complete
  • Effort: 6 hrs / week
  • Skills: Text Mining, Python Programming, Pandas, Matplotlib, Numpy, Data Cleansing, Data VirtualizationData Visualization (DataViz), Machine Learning (ML) Algorithms, Machine Learning, Scikit-Learn, Natural Language Toolkit (NLTK)

Data Scientist NanodegreeIn this Udacity nanodegree you will master the skills necessary to become a successful Data Scientist. You will work on projects designed by industry experts, and learn to run data pipelines, design experiments, build recommendation systems, and deploy solutions to the cloud. This program requires previous knowledge of Python programming, SQL, Probability and Statistics, and Machine Learning concepts (supervised and unsupervised methods). 

Nanodegree highlights:

  • Includes 5 courses
  • Duration: 4 months
  • Effort: 10 hrs / week
  • Skills: Machine Learning, Deep Learning, Software Engineering

Johns Hopkins University logoThis 10-course Coursera Specialization offered by Johns Hopkins University, covers the concepts and tools a learner will need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you will apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material, which  will allow you to launch your career in Data Science. This is one of the most popular Data Science programs out there!

Specialization highlights:

  • 100% Online Self-Paced
  • Includes 10 courses
  • Duration: 11 months to complete
  • Effort: 7 hrs / week
  • Skills: Github, Machine Learning, R Programming, Regression Analysis, Data Science, Rstudio, Data Analysis, Debugging, Data Manipulation, Regular Expression (REGEX), Data Cleansing, Cluster Analysis

Harvard University logoThe edX Data Science program offered by HarvardX, provides you with the necessary knowledge base and useful skills to tackle real-world data analysis challenges. This Professional Certificate covers concepts such as probability, inference, regression, and machine learning and helps you develop an essential skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git and GitHub, and reproducible document preparation with RStudio. It also includes case studies, such as: Trends in World Health and Economics, US Crime Rates, The Financial Crisis of 2007-2008, Election Forecasting, Building a Baseball Team, and Movie Recommendation Systems.

Professional Certificate highlights:

  • 100% Online Self-Paced
  • Includes 9 skill-building courses
  • Duration: 1 year 5 months
  • Effort: 2-3 hrs / week
  • Skills: R programming, ggplot2, GitHub, Unix/Linux, RStudio, Probability, Statistics, Data Visualization, Machine Learning

Become a Data ScientistThis LinkedIn Learning path will support you in developing a career in Data Science. It will teach you the fundamental stages of data science work, from Statistics and Systems Engineering to Data Mining and Machine Learning. In a nutshell, you will: build a solid foundational understanding of statistics, which is necessary for any data science-related field; discover the many categories of job specialization within Data Science; and learn how to source, explore, and communicate with data through graphs and statistics.


Learning Path highlights:

  • Online Self-Paced 
  • Includes 8 courses
  • Duration: 17 hrs 13 min
  • Skills: Data Visualization, Data Analysis

Data Scientist with RIn this DataCamp Career Track you will learn how the R programming language allows you to import, clean, manipulate, and visualize data, all integral skills for any aspiring data professional/researcher. Through interactive exercises, you will get hands-on with some of the most popular R packages, including ggplot2 and tidyverse packages like dplyr and readr. You will be working with real-world datasets to learn the statistical and machine learning techniques you need to write your own functions and perform cluster analysis. In a nutshell, this track will allow you to grow your R skills, and begin your journey to becoming a confident data scientist.


Career Track highlights:
 

  • Includes 19 courses
  • Duration: 76 hours
  • Skills: Data Visualization, Data Analysis

Monash University logoIn this FutureLearn microcredential, you’ll work through practical programming exercises in R language to learn the process of tidying, harvesting and wrangling data and applying statistical models to simulate complex functions that solve a broad range of problems. You will learn how to develop effective data visualisations for decision-making, and communicating your message to others. You’ll also explore the essential ethical, legal and organisational issues of data collection and management. By completing this program, you will have gained the required skills to apply for roles as a data scientist or use the acquired knowledge to enhance your current organisation.

Microcredential highlights:

  • 100% Online
  • Enrolment: every few months
  • Includes 3 courses
  • Duration: 12 weeks
  • Skills: Data wrangling, R programming, Developing data analysis workflows, Work with and visualise spatial and temporal data, Developing statistical models, Harvesting data, Tidying data, Data collection methods, Data visualisation, Data analysis

The Data Science Course 2020The Data Science Course 2020 course is an effort to create the most effective, time-efficient, and structured data science training available online. It claims to be the first training program that solves the biggest challenge to entering the data science field, having all the necessary resources in one place. The course focuses to teach topics that flow smoothly and complement each other. It teaches you everything you need to know to become a data scientist at a fraction of the cost of traditional programs. In a nutshell, the course covers all the following necessary skills: Intro to Data and Data Science; Mathematics; Statistics; Python; Tableau; Advanced Statistics; and Machine & Deep Learning.  

Course highlights:

  • 100% Online
  • 28.5 hours on-demand video
  • Full lifetime access
  • Skills: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

10 Best AI & Machine Learning Courses

This is a selection of the 10 best AI & Machine Learning courses across several e-learning platforms. Depending on the platform, some courses/programs require either a one-time purchase or a monthly subscription. The list below will be updated regularly with the most popular courses in AI & Machine Learning.

Machine Learning Courses

Machine Learning Engineer NanodegreeIn this Udacity nanodegree, offered in collaboration with Kaggle and AWS, you will learn advanced machine learning techniques and algorithms as well as how to package and deploy your models to a production environment. You will gain practical experience using Amazon SageMaker to deploy trained models to a web application and evaluate the performance of your models. A/B test models and learn how to update the models as you gather more data, an important skill in industry. This program requires an intermediate level of Python programming and knowledge of Machine Learning algorithms. 

Nanodegree highlights:

  • Includes 4 courses
  • Duration: 3 months
  • Effort: 10 hrs / week
  • Skills: Machine Learning, Supervised Learning, Unsupervised Learning, Deep Learning

Harvard University logoThe edX program in Computer Science for Artificial Intelligence, offered by HarvardX, takes a deep dive into the concepts and algorithms at the foundation of modern artificial intelligence. This series will lead you through the most popular undergraduate course at Harvard, where you will learn the common programming languages, then carries that foundation through CS50’s Introduction to Artificial Intelligence with Python. Through hands-on projects, you’ll gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence. Last but not least,  the knowledge gained in AI principles will allow you to design intelligent systems of their own.

Professional Certificate highlights:

  • 100% Online Self-Paced
  • Includes 2 skill-building courses
  • Duration: 5 months
  • Effort: 7-22 hrs / week
  • Skills: Machine Learning, Reinforcement learning, Computer Programming, Artificial intelligence, Graph search algorithms

deeplearning.ai logoTensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches you applied machine learning skills with TensorFlow so you can build and train powerful models. In other words, in this hands-on four-course Professional Certificate program, you will learn the necessary tools to build scalable AI-powered applications with TensorFlow. After finishing this program, you will be able to apply your new TensorFlow skills to a wide range of problems and projects.

Professional Certificate highlights:

  • 100% Online Self-Paced
  • Includes 4 skill-building courses
  • Duration: 4 months
  • Effort: 5 hrs / week
  • Skills: Computer Vision, Convolutional Neural Network, Machine Learning, Natural Language Processing, Tensorflow, Inductive Transfer, Augmentation, Dropouts, Tokenization, RNNs, Forecasting, Time Series

Columbia University logoIn this MicroMasters program you will gain expertise in one of the most fascinating and fastest growing areas of computer science through an innovative online program in Artificial Intelligence and its applications. This MicroMasters program from Columbia University will give you a rigorous, advanced, professional, graduate-level foundation in Artificial Intelligence. The program represents 25% of the coursework toward a Master’s degree in Computer Science at Columbia. These courses are instructional-led and each course has 10-12 weeks of lecture plus an additional final exam week. If you are interested in completing the full MicroMasters program on edX, there is no time limit in which you must complete all the courses in the program. Currently, the courses are offered twice a year, in the spring and fall term.

MicroMasters highlights:

  • Online Instructor-led
  • Includes 4 graduate-level courses
  • Duration: 1 year
  • Effort: 8-10 hrs / week
  • Skills: AI, Neural Networks, Machine Learning, Robotics, Animation and CGI Motion

Become a Machine Learning SpecialistThis LinkedIn Learning path shows how machine learning algorithms work and how to design them yourself. There is a lot to learn in this rapidly growing and highly recruited-for field, and these courses will give you an extremely solid skill set.In a nutshell, you will: explore the concepts and techniques behind designing machine learning algorithms; learn how recommendation systems work and how to build them; and master how to design machine solutions for different applications.

Learning Path highlights:

  • 100% Online Self-paced
  • Includes 9 courses
  • Duration: 17 hrs 18 min
  • Skill: Data Science

In the Udacity Machine Learning Engineer for Microsoft Azure Nanodegree, offered in collaboration with Microsoft, you will be able to enhance your skills by building and deploying sophisticated machine learning solutions using popular open source tools and frameworks, and gain practical experience running complex machine learning tasks using the built-in Azure labs accessible inside the Udacity classroom. Prior experience with Python, Machine Learning, and Statistics is a prerequisite for taking this program.

Nanodegree highlights:

  • Includes 3 courses
  • Duration: 3 months
  • Effort: 5-10 hrs / week
  • Skills: Azure Machine Learning, Azure Machine Learning SDK, Automation with Pipelines, Automated ML, Machine Learning Operations

deeplearning.ai logoNatural Language Processing (NLP) uses algorithms to understand and manipulate human language. This technology is one of the most broadly applied areas of machine learning. As AI continues to expand, so will the demand for professionals skilled at building models that analyze speech and language, uncover contextual patterns, and produce insights from text and audio. This Coursera Specialization, offered by DeepLearning.AI, will prepare you to design NLP applications that perform question-answering and sentiment analysis, create tools to translate languages and summarize text, and even build chatbots. These and other NLP applications are going to be at the forefront of the coming transformation to an AI-powered future.

Specialization highlights:

  • 100% Online Self-Paced
  • Includes 4 courses
  • Duration: 4 months
  • Effort: 6 hrs / week
  • Skills: Sentiment Analysis, Siamese Networks, Hidden Markov Model, Transformers, Attention Models, Machine Translation, Word Embeddings, Locality-Sensitive Hashing, Vector Space Models, Word2vecParts-of-Speech Tagging, N-gram Language Models

Machine Learning Scientist with RThis DataCamp Career Track will equip you with the essential skills to land a job as a machine learning scientist. It will allow you to improve your R programming skill set with the toolbox to perform supervised and unsupervised learning. You will also learn how to process data for modeling, train your models, visualize your models and assess their performance, and tune their parameters for better performance. In the process, you will get an introduction to Bayesian statistics, natural language processing, and Spark.

Career Track highlights:

  • 100% Online Self-Paced
  • Includes 15 courses
  • Duration: 61 hours
  • Skills: R programming, Machine Learning, Supervised Learning, Unsupervised Learning, Natural Language, Bayesian Statistics Processing, Spark

Master the Fundamentals of AI and Machine LearningAfter taking this LinkedIn Learning path, you will have a mastery of the concepts and future directions of artificial intelligence and machine learning. You will definitely be able to make more informed decisions and contributions in your work envrionment. In a nutshell, you will: gain a clear and detailed understanding of how AI and machine learning work; learn how leading companies are using AI and machine learning to change the way they do business; and learn how the next generation of thinking about AI is addressing issues of accountability, security, and explainability.

Learning Path highlights:

  • 100% Online Self-paced
  • Includes 9 courses
  • Duration: 11 hrs 59 min
  • Skills: Neural Networks, Machine Learning

Machine Learning A-Z™: Hands-On Python & R In Data ScienceThis Udemy course has been designed by two professional Data Scientists who want to share their knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way. The course walks you step-by-step into the world of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. This course is fun and exciting, but at the same time, it dives deep into Machine Learning topics such as: data preprocessing, regression, classification, reinforcement learning, deep learning, natural language processing, model selection and more. Moreover, the course is packed with practical exercises that are based on real-life examples, and both Python and R codes templates are provided to use on your own projects.

Course highlights:

  • 100% Online
  • 44 hours on-demand video
  • Full lifetime access
  • Skills: Python Programming, R Programming, Machine Learning