IBM provides a wide variety of technology and consulting services, a broad portfolio of collaborative middleware,predictive analytics, software development and system management ; and the most developed servers and supercomputers in the world.
Utilizing its business consulting, technology and R&D expertise, IBM helps clients become “smarter” as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.In this post,we take look at curated compilation of courses offered by IBM.
- #1.Advanced Data Science with IBM
- #2.Applied Data Science
- #3.IBM Data Science Professional Certificate
- #4.IBM Microservices
- #5.Introduction to Data Science
- #6.Advanced Data Science Capstone
- #7.Advanced Machine Learning and Signal Processing
- #8.Applied AI with DeepLearning
- #9.Applied Data Science Capstone
- #10.Data Analysis with Python
- #11.Data Science Methodology
- #12.Data Visualization with Python
- #13.Databases and SQL for Data Science
- #14.Developing and Deploying Microservices with Microclimate
- #15.Fundamentals of Scalable Data Science
- #16.Building AI Powered Chatbots Without Programming
- #17.IBM Cloud Private: Deploying Microservices with Kubernetes
- #18.IBM Cloud: Deploying Microservices with Kubernetes
- #19.IBM Customer Engagement Specialist Professional Certificate
- #20.Microservices – Fundamentals
- #21.Open Source tools for Data Science
- #22.Python for Data Science and AI
- #23.Machine Learning with Python
- #24.What is Data Science?
- #25.AI Foundations for Everyone
- #26.Applied AI: Artificial Intelligence with IBM Watson
- #27.IBM Artificial Intelligence Professional Certificate
- #28.Building AI Applications with Watson APIs
- #29.Getting Started with AI using IBM Watson
- #30.Introduction to Artificial Intelligence (AI)
- #31.Introduction to Computer Vision with Watson and OpenCV
- #32.IT Fundamentals for Cybersecurity
- #33.Cybersecurity Roles, Processes & Operating System Security
- #34.Network Security & Database Vulnerabilities
- #35.Introduction to Cybersecurity Tools & Cyber Attacks
- #36.Cybersecurity Compliance Framework & System Administration
- #Useful Resources
All these courses are completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free.
As a coursera certified specialization completer you will have a proven deep understanding on massive parallel data processing, data exploration and visualization, and advanced machine learning & deep learning. You’ll understand the mathematical foundations behind all machine learning & deep learning algorithms. You can apply knowledge in practical use cases, justify architectural decisions, understand the characteristics of different algorithms, frameworks & technologies & how they impact model performance & scalability. If you choose to take this specialization and earn the Coursera specialization certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging.
This is an action-packed specialization is for data science enthusiasts who want to acquire practical skills for real world data problems. It appeals to anyone interested in pursuing a career in Data Science, and already has foundational skills (or has completed the Introduction to Applied Data Science specialization). You will learn Python – no prior programming knowledge necessary. You will then learn data visualization and data analysis. Through our guided lectures, labs, and projects you’ll get hands-on experience tackling interesting data problems. Make sure to take this specialization to solidify your Python and data science skills before diving deeper into big data, AI, and deep learning. Upon completing all courses in the specialization and receiving the Specialization certificate, you will also receive an IBM Badge recognizing you as a Specialist in Applied Data Science. LIMITED TIME OFFER: Subscription is only $39 USD per month and gives you access to graded materials and a certificate.
Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming. This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Data Science or Machine Learning. This program consists of 9 courses providing you with latest job-ready skills and techniques covering a wide array of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets. It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. We start small, re-enforce applied learning, and build up to more complex topics. Upon successfully completing these courses you will have done several hands-on assignments and built a portfolio of data science projects to provide you with the confidence to plunge into an exciting profession in Data Science. In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Data Science. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
This specialization is intended for application developers and network administrators seeking to understand the benefits of microservices architecture and container-based applications. The student learns how to develop and deploy microservices applications with Kubernetes on IBM Cloud and IBM Cloud Private via a continuous release pipeline.
In this Specialization learners will develop foundational Data Science skills to prepare them for a career or further learning that involves more advanced topics in Data Science. The specialization entails understanding what is Data Science and the various kinds of activities that a Data Scientist performs. It will familiarize learners with various open source tools, like Jupyter notebooks, used by Data Scientists. It will teach you about methodology involved in tackling data science problems. The specialization also provides knowledge of relational database concepts and the use of SQL to query databases. Learners will complete hands-on labs and projects to apply their newly acquired skills and knowledge. Upon receiving the certificate for completion of the specialization, you will also receive an IBM Badge as a Specialist in Data Science Foundations. LIMITED TIME OFFER: Subscription is only $39 USD per month and gives you access to graded materials and a certificate.
This project completer has proven a deep understanding on massive parallel data processing, data exploration and visualization, advanced machine learning and deep learning and how to apply his knowledge in a real-world practical use case where he justifies architectural decisions, proves understanding the characteristics of different algorithms, frameworks and technologies and how they impact model performance and scalability. Please note: You are requested to create a short video presentation at the end of the course. This is mandatory to pass. You don’t need to share the video in public.
>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< This course, Advanced Machine Learning and Signal Processing, is part of the IBM Advanced Data Science Specialization which IBM is currently creating and gives you easy access to the invaluable insights into Supervised and Unsupervised Machine Learning Models used by experts in many field relevant disciplines. We’ll learn about the fundamentals of Linear Algebra to understand how machine learning modes work. Then we introduce the most popular Machine Learning Frameworks for python Scikit-Learn and SparkML. SparkML is making up the greatest portion of this course since scalability is key to address performance bottlenecks. We learn how to tune the models in parallel by evaluating hundreds of different parameter-combinations in parallel. We’ll continuously use a real-life example from IoT (Internet of Things), for exemplifying the different algorithms. For passing the course you are even required to create your own vibration sensor data using the accelerometer sensors in your smartphone. So you are actually working on a self-created, real dataset throughout the course. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging.
>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< This course, Applied Artificial Intelligence with DeepLearning, is part of the IBM Advanced Data Science Certificate which IBM is currently creating and gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines. We’ll learn about the fundamentals of Linear Algebra and Neural Networks. Then we introduce the most popular DeepLearning Frameworks like Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML. Keras and TensorFlow are making up the greatest portion of this course. We learn about Anomaly Detection, Time Series Forecasting, Image Recognition and Natural Language Processing by building up models using Keras on real-life examples from IoT (Internet of Things), Financial Marked Data, Literature or Image Databases. Finally, we learn how to scale those artificial brains using Kubernetes, Apache Spark and GPUs. IMPORTANT: THIS COURSE ALONE IS NOT SUFFICIENT TO OBTAIN THE “IBM Watson IoT Certified Data Scientist certificate”. You need to take three other courses where two of them are currently built. The Specialization will be ready late spring, early summer 2018 Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. If you’re already an expert, this peep under the mental hood will give your ideas for turbocharging successful creation and deployment of DeepLearning models. If you’re struggling, you’ll see a structured treasure trove of practical techniques that walk you through what you need to do to get on track. If you’ve ever wanted to become better at anything, this course will help serve as your guide. Prerequisites: Some coding skills are necessary. Preferably python, but any other programming language will do fine. Also some basic understanding of math (linear algebra) is a plus, but we will cover that part in the first week as well. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging.
This capstone project course will give you a taste of what data scientists go through in real life when working with data. You will learn about location data and different location data providers, such as Foursquare. You will learn how to make RESTful API calls to the Foursquare API to retrieve data about venues in different neighborhoods around the world. You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code. You will utilize Python and its pandas library to manipulate data, which will help you refine your skills for exploring and analyzing data. Finally, you will be required to use the Folium library to great maps of geospatial data and to communicate your results and findings. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more! Topics covered: 1) Importing Datasets 2) Cleaning the Data 3) Data frame manipulation 4) Summarizing the Data 5) Building machine learning Regression models 6) Building data pipelines Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts: Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don’t have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand. This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand. Accordingly, in this course, you will learn: – The major steps involved in tackling a data science problem. – The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment. – How data scientists think! LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
A picture is worth a thousand words”. We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data. One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions. The main goal of this Data Visualization with Python course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.”
Much of the world’s data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for communicating with and extracting data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist. The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment. The emphasis in this course is on hands-on and practical learning. As such, you will work with real databases, real data science tools, and real-world datasets. You will create a database instance in the cloud. Through a series of hands-on labs you will practice building and running SQL queries. You will also learn how to access databases from Jupyter notebooks using SQL and Python. No prior knowledge of databases, SQL, Python, or programming is required. Anyone can audit this course at no-charge. If you choose to take this course and earn the Coursera course certificate, you can also earn an IBM digital badge upon successful completion of the course. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
This course provides an introduction to Microclimate, an end-to-end development environment that lets you rapidly create, edit, and deploy applications that run in containers. Microclimate can be installed locally, or on IBM Cloud Private, where you can create a pipeline for continuous integration and delivery. In this course, you learn how to quickly set up a development environment for working with Microclimate, and import a sample application. Using the Integrated Jenkins pipeline and Github, you also learn how to deploy a microservice application to IBM Cloud Private. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link http://ibm.biz/badging.
Apache Spark is the de-facto standard for large scale data processing. This is the first course of a series of courses towards the IBM Advanced Data Science Specialization. We strongly believe that is is crucial for success to start learning a scalable data science platform since memory and CPU constraints are to most limiting factors when it comes to building advanced machine learning models. In this course we teach you the fundamentals of Apache Spark using python and pyspark. We’ll introduce Apache Spark in the first two weeks and learn how to apply it to compute basic exploratory and data pre-processing tasks in the last two weeks. Through this exercise you’ll also be introduced to the most fundamental statistical measures and data visualization technologies. This gives you enough knowledge to take over the role of a data engineer in any modern environment. But it gives you also the basis for advancing your career towards data science. Please have a look at the full specialization curriculum: https://www. coursera.org/specializations/advanced-data-science-ibm If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging. After completing this course, you will be able to: Describe how basic statistical measures, are used to reveal patterns within the data Recognize data characteristics, patterns, trends, deviations or inconsistencies, and potential outliers. Identify useful techniques for working with big data such as dimension reduction and feature selection methods Use advanced tools and charting libraries to: o improve efficiency of analysis of big-data with partitioning and parallel analysis o Visualize the data in an number of 2D and 3D formats (Box Plot, Run Chart, Scatter Plot, Pareto Chart, and Multidimensional Scaling) For successful completion of the course, the following prerequisites are recommended: Basic programming skills in python Basic math Basic SQL (you can get it easily from https://www. coursera.org/learn/sql-data-science if needed) In order to complete this course, the following technologies will be used: (These technologies are introduced in the course as necessary so no previous knowledge is required.) Jupyter notebooks (brought to you by IBM Watson Studio for free) ApacheSpark (brought to you by IBM Watson Studio for free) Python This course takes four weeks, 4-6h per week
This course will teach you how to create useful chatbots without the need to write any code. Leveraging IBM Watson’s Natural Language Processing capabilities, you’ll learn how to plan, implement, test, and deploy chatbots that delight your users, rather than frustrate them. True to our promise of not requiring any code, you’ll learn how to visually create chatbots with Watson Assistant (formerly Watson Conversation) and how to deploy them on your own website through a handy WordPress plugin. Don’t have a website? No worries, one will be provided to you. Chatbots are a hot topic in our industry and are about to go big. New jobs requiring this specific skill are being added every day, consultants demand premium rates, and the interest in chatbots is quickly exploding. Gartner predicts that by 2020, 85% of customer interactions with the enterprise will be through automated means (that’s chatbots and related technologies). Here is your chance to learn this highly in demand set of skills with a gentle introduction to the topic that leaves no stone unturned.
IBM Cloud Private is an application platform for developing and managing on-premises, containerized applications. It includes the container orchestrator Kubernetes, a private image repository, a management console, and monitoring frameworks. In this course, you learn how to install and configure IBM Cloud Private components in your environment, and how to prepare microservices applications for deployment. The ideal candidate for this course has a basic understanding of cloud computing, and a working knowledge of developing microservices. Experience with using Docker, and familiarity with YAML is also a plus. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link http://ibm.biz/badging.
In this course, you learn how to deploy and manage Microservices applications with Kubernetes. The course uses video lectures, readings, and hands-on tutorials to teach you the skills needed to get started with Kubernetes. You also learn about securing and managing a Kubernetes cluster, and how to plan your Kubernetes cluster for deployment to IBM Cloud. To complete the hands-on tutorials in this course, you must use your own computing device and install the required software, as directed in the tutorials. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link http://ibm.biz/badging.
There are a growing number of exciting, well-paying jobs in today’s tech industry that do not require a traditional college degree. And one of the hottest areas with high demand is in IT customer service and support. It’s a perfect entry point to start your career in IT with a multitude of job openings ranging from onsite or remote help desk work to customer care or client support. We can help you get there with the IBM Customer Engagement Specialist Certificate Program. We will help you to build the knowledge and develop the skills needed to be a successful Customer engagement specialist: Communication Skills which focus on clear concise communication and listening. Appropriate empathetic behavior such as such as patience, curiosity and willingness to help. Problem solving to research an issue and help determine an appropriate resolution. Process adherence to ensure the proper flow and Service Level Agreements are met. The course is divided into 4 modules and you will be assessed and awarded badges along the way! Earn the IBM Soft Skills badge after completing the Communication Skills and Personality modules and the IBM Call Management badge after completing the Problem Solving and Process Control modules. The course also includes interactive training including labs to reinforce all of the components above. At the conclusion of the course, you will receive an email from Coursera with the information that you will need in order to take the final certificate exam. Passing the IBM New Collar: Customer Engagement V1 exam is required in order to receive the official IBM Customer Engagement Specialist Certificate. The exam consists of 48 questions which represent the learning from all 4 modules of the course. You will have an hour to complete the exam. This exam can be taken at any Pearson VUE worldwide or through online proctored testing in select countries for $50.
In enterprise environments, the architectural style of microservices is gaining momentum. In this course, you will learn why microservices are well-suited to modern cloud environments which require short development and delivery cycles. You will learn the characteristics of microservices. You will compare the microservice architecture with monolithic style, emphasizing why microservices are well suited to continuous delivery. While microservices are more modular to develop and may look simpler, you will discovery that the complexity does not go away, it shifts. An inevitable organizational complexity comes along with many small interacting pieces. Managing, monitoring, logging, and updating microservices creates a greater operational complexity. In this course you learn about the tools necessary to successfully deploy, manage and monitor microservice based applications. After taking this course, you will have a much better understanding of why microservices are so well suited to cloud environments, the DevOps environments in which microservices run and the tools to manage the complexity that microservices bring to the operational and production environment. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link http://ibm.biz/badging.
What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you’ll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours. Module 1 – Python Basics o Your first program o Types o Expressions and Variables o String Operations Module 2 – Python Data Structures o Lists and Tuples o Sets o Dictionaries Module 3 – Python Programming Fundamentals o Conditions and Branching o Loops o Functions o Objects and Classes Module 4 – Working with Data in Python o Reading files with open o Writing files with open o Loading data with Pandas o Numpy Finally, you will create a project to test your skills. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Second, you will get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms. In this course, you practice with real-life examples of Machine learning and see how it affects society in ways you may not have guessed! By just putting in a few hours a week for the next few weeks, this is what you’ll get. 1) New skills to add to your resume, such as regression, classification, clustering, sci-kit learn and SciPy 2) New projects that you can add to your portfolio, including cancer detection, predicting economic trends, predicting customer churn, recommendation engines, and many more. 3) And a certificate in machine learning to prove your competency, and share it anywhere you like online or offline, such as LinkedIn profiles and social media. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science. In this course, we will meet some data science practitioners and we will get an overview of what data science is today. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
Artificial Intelligence (AI) is no longer science fiction. It is rapidly permeating all industries and having a profound impact on virtually every aspect of our existence. Whether you are an executive, a leader, an industry professional, a researcher, or a student – understanding AI, its impact and transformative potential for your organization and our society is of paramount importance. This specialization is designed for those with little or no background in AI, whether you have technology background or not, and does not require any programming skills. It is designed to give you a firm understanding of what is AI, its applications and use cases across various industries. You will become acquainted with terms like Machine Learning, Deep Learning and Neural Networks. Furthermore, it will familiarize you with IBM Watson AI services that enable any business to quickly and easily employ pre-built AI smarts to their products and solutions. You will also learn about creating intelligent virtual assistants and how they can be leveraged in different scenarios. By the end of this specialization, learners will have had hands-on interactions with several AI environments and applications, and have built and deployed an AI enabled chatbot on a website – without any coding.
Artificial Intelligence (AI) is transforming our world. Whether you’re a student, developer, or a technology consultant, understanding AI and knowing how to create AI powered applications can give you an edge. This Specialization will give you a firm understanding of AI, its applications, and its use cases. You will become familiar with IBM Watson AI services and APIs. If you have no programming background, you will be able to create AI driven chatbots as well as pick up practical Python skills to work with AI. The courses will also enable you to apply pre-built AI smarts to your products and solutions. A learner with no prior knowledge of AI will learn to design, build, and deploy AI-powered applications on the web. Rather than create complex AI algorithms and interfaces from scratch, learners will use IBM Watson AI services and APIs to create smart applications with minimal coding. By the end of this Specialization, learners will complete several projects that showcase proficiency in applied AI.
The rapid pace of innovation in Artificial Intelligence (AI) is creating enormous opportunity for transforming entire industries and our very existence. It is expected to generate over 50 million net new jobs in the next few years alone. Whether you are a seasoned industry professional such as a developer or a data scientist, a student looking to enter the workforce, or an existing AI practitioner interested in learning the latest in AI innovation and technologies, this AI Professional Certificate from IBM will enable you to future proof your career and stay ahead of your competition. You will get a firm understanding of what is AI, its usecases, become familiar with Watson AI services, and apply your skills to build AI applications. Furthermore you will get an applied understanding of Machine Learning and Deep Learning. You will practice these skills hands-on and build AI models with modern tools and frameworks like Scikitlearn, Keras, PyTorch and Tensorflow. By the end of this Professional Certificate, you will have completed several projects showcasing your proficiency in Applied AI, Machine Learning and Deep Learning. No prior knowledge of AI or programming is necessary.
A learner will be able to write an application that leverages multiple Watson AI services (Discovery, Speech to Text, Assistant, and Text to Speech). By the end of the course, they’ll learn best practices of combining Watson services, and how they can build interactive information retrieval systems with Discovery + Assistant.
In this course you will learn how to quickly and easily get started with Artificial Intelligence using IBM Watson. You will understand how Watson works, become familiar with its use cases and real life client examples, and be introduced to several of Watson AI services from IBM that enable anyone to easily apply AI and build smart apps. You will also work with several Watson services to demonstrate AI in action. This course does not require any programming or computer science expertise and is designed for anyone whether you have a technical background or not.
In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. You will also demonstrate AI in action with a mini project. This course does not require any programming or computer science expertise and is designed to introduce the basics of AI to anyone whether you have a technical background or not.
Computer Vision is one of the most exciting fields in Machine Learning and AI. It has applications in many industries such as self-driving cars, robotics, augmented reality, face detection in law enforcement agencies. In this beginner-friendly course you will understand about computer vision, and will learn about its various applications across many industries. As part of this course you will utilize Python, Watson AI, and OpenCV to process images and interact with image classification models. You will also build, train, and test your own custom image classifiers. This is a hands-on course and involves several labs and exercises. All the labs will be performed on the Cloud and you will be provided access to a Cloud environment completely free of charge. At the end of the course, you will create your own computer vision web app and deploy it to the Cloud. This course does not require any prior Machine Learning or Computer Vision experience, however some knowledge of Python programming language is necessary.
There are a growing number of exciting, well-paying jobs in today’s security industry that do not require a traditional college degree. Forbes estimates that there will be as many as 3.5 million unfilled positions in the industry worldwide by 2021! One position with a severe shortage of skills is as a junior cybersecurity analyst. This specialization will provide you with the basics you need to get started. Throughout this specialization, you will learn concepts around cybersecurity tools and processes, system administration, operating system and database vulnerabilities, types of cyber attacks and basics of networking. You will also gain knowledge around important topics such as cryptography and digital forensics. This specialization is truly an international offering from IBM with experts from the United States, Costa Rica, Canada and Italy. These instructors are architects, Security Operation Center (SOC) analysts, and distinguished engineers who work with cybersecurity in their day to day lives at IBM. They will share their skills which they need to secure IBM and its clients security systems. The completion of this specialization also makes you eligible to earn the IT Fundamentals for Cybersecurity IBM digital badge. More information about the badge can be found here: https://www. youracclaim.com/org/ibm/badge/cybersecurity-it-fundamentals-specialist
This course gives you the background needed to understand basic Cybersecurity around people. process and technology. You will learn: â— Understand the key cybersecurity roles within an Organization. â— List key cybersecurity processes and an example of each process. â— Describe the architecture, file systems, and basic commands for multiple operating systems including Windows, Mac/OS, Linux and Mobile. â— Understand the concept of Virtualization as it relates to cybersecurity Finally, you will begin to learn about organizations and resources to further research cybersecurity issues in the Modern era. This course is intended for anyone who wants to gain a basic understanding of Cybersecurity or as the second course in a series of courses to acquire the skills to work in the Cybersecurity field as a Jr Cybersecurity Analyst. The completion of this course also makes you eligible to earn the Cybersecurity Roles, Processes & Operating System Security IBM digital badge. More information about the badge can be found here: https://www. youracclaim.com/org/ibm/badge/cybersecurity-roles-processes-operating-system-security
This course gives you the background needed to understand basic network security. You will learn the about Local Area Networks, TCP/IP, the OSI Framework and routing basics. You will learn how networking affects security systems within an organization. You will learn the network components that guard an organization from cybersecurity attacks. In addition to networking, you will learn about database vulnerabilities and the tools/knowledge needed to research a database vulnerability for a variety of databases including SQL Injection, Oracle, Mongo and Couch. You will learn about various security breach types associated with databases and organizations that define standards and provide tools for cybersecurity professionals. This course is intended for anyone who wants to gain a basic understanding of Network Security/Database Vulnerabilities or as the fourth course in a series of courses to acquire the skills to work in the Cybersecurity field as a Jr Cybersecurity Analyst.
This course gives you the background needed to understand basic Cybersecurity. You will learn the history of Cybersecurity, types and motives of cyber attacks to further your knowledge of current threats to organizations and individuals. Key terminology, basic system concepts and tools will be examined as an introduction to the Cybersecurity field. You will learn about critical thinking and its importance to anyone looking to pursue a career in Cybersecurity. Finally, you will begin to learn about organizations and resources to further research cybersecurity issues in the Modern era. This course is intended for anyone who wants to gain a basic understanding of Cybersecurity or as the first course in a series of courses to acquire the skills to work in the Cybersecurity field as a Jr Cybersecurity Analyst. The completion of this course also makes you eligible to earn the Introduction to Cybersecurity Tools & Cyber Attacks IBM digital badge. More information about the badge can be found https://www. youracclaim.com/org/ibm/badge/introduction-to-cybersecurity-tools-cyber-attacks
This course gives you the background needed to understand the key cybersecurity compliance and industry standards. This knowledge will be important for you to learn no matter what cybersecurity role you would like to acquire or have within an organization. You will learn the basic commands for user and server administration as it relates to security. You will need this skill to be able to understand vulnerabilities within your organizations operating systems. You will learn the concepts of endpoint security and patch management. Both of these topics are important to keep systems current to avoid cybersecurity incidents against an organization. Finally you will learn in depth skills around cryptography and encryption to understand how these concepts affect software within a company. This course is intended for anyone who wants to gain a basic understanding of Security Frameworks, Compliance, endpoint management, encryption or cryptography or as the third course in a series of courses to gain the skill as a Jr Cybersecurity analyst.
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