Data Science Methodology

 

What you'll learn

Describe what a data science methodology is and why data scientists need a methodology.

Apply the six stages in the Cross-Industry Process for Data Mining (CRISP-DM) methodology to analyze a case study.

Evaluate which analytic model is appropriate among predictive, descriptive, and classification models used to analyze a case study.

Determine appropriate data sources for your data science analysis methodology.

Join Free:Data Science Methodology

There are 4 modules in this course

If there is a shortcut to becoming a Data Scientist, then learning to think and work like a successful Data Scientist is it. In this course, you will learn and then apply this methodology that you can use to tackle any Data Science scenario. You’ll explore two notable data science methodologies, Foundational Data Science Methodology, and the six-stage CRISP-DM data science methodology, and learn how to apply these data science methodologies. Most established data scientists follow these or similar methodologies for solving data science problems.

Begin by learning about forming the business/research problem Learn how data scientists obtain, prepare, and analyze data. Discover how applying data science methodology practices helps ensure that the data used for problem-solving is relevant and properly manipulated to address the question. Next, learn about building the data model, deploying that model, data storytelling, and obtaining feedback You’ll think like a data scientist and develop your data science methodology skills using a real-world inspired scenario through progressive labs hosted within Jupyter Notebooks and using Python.

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Introduction to Web Development with HTML, CSS, JavaScript

 

What you'll learn

Describe the Web Application Development Ecosystem and terminology like front-end developer, back-end, server-side, and full stack.

Identify the developer tools and integrated development environments (IDEs) used by web developers. 

Create and structure basic web pages using HTML and style them with CSS. 

Develop dynamic web pages with interactive features using JavaScript.

Join Free:Introduction to Web Development with HTML, CSS, JavaScript

There are 5 modules in this course

Want to take the first steps to become a Web Developer? This course will help you discover the languages, frameworks, and tools that you will need to create interactive and engaging websites right from the beginning.  

You will begin by learning about the roles of front-end, back-end, and full-stack developers and how they work together on development projects. Through this, you will also become familiar with the terminology and skills needed in your career as a web developer.  

Next, you will explore the languages needed for developing websites or applications. You will gain a thorough understanding of HTML and CSS and learn how a combination of both technologies can help developers create the structure and style of their websites.  

Finally, you will learn how JavaScript can make your webpages dynamic with features that include interactive forms, dynamic content modification, and sophisticated menu systems. 

By learning the fundamentals of HTML5, CSS, and JavaScript you will be able to combine them to:  

- create the basic structure of a website  

- create format and layout for web applications 

- enhance your website and create rich, interactive applications 

- increase user interactivity and enhance user experience 

- give your website a real wow factor! 

In this course you will practice what you learn with numerous hands-on labs. Lastly, you will complete a final project where you will create a webpage to showcase your skills and have a great addition to your portfolio!

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Introduction to Cybersecurity Essentials

 

What you'll learn

Recognize the importance of data security, maintaining data integrity, and confidentiality

Demonstrate the installation of software updates and patches

Identify preferred practices for authentication, encryption, and device security

Discuss types of security threats, breaches, malware, social engineering, and other attack vectors

Join Free:Introduction to Cybersecurity Essentials

There are 4 modules in this course

With this beginner friendly course, learn fundamental Cybersecurity skills that are crucial for anyone using computing devices and connecting to the Internet.  

You will first learn to recognize common security threats and risks that individuals and organizations may face, such as theft, tampering, and destruction of sensitive information. You’ll then discover the characteristics of cyber-attacks and learn how you can employ best practices to guard against them.  

Next, you’ll learn about the best practices against cyberattacks. These include using strong passwords, good password management, and multi-factor authentication. You’ll learn ways in which you can strengthen your security plan with techniques like device hardening, encryption and more. 

You’ll then learn about safe browsing practices. You’ll gain an understanding of why you must practice safe browsing; to protect yourself against hackers, phishing, identity theft, security leaks, privacy issues and more. You’ll also explore methods for securing and managing confidential information. Then, discover how to configure browsers to help reduce security breaches. 

Throughout this course you will complete many hands-on labs which will enhance your understanding of course material. At the end of this course, you will have the opportunity to complete a final project where you will demonstrate your proficiency in cybersecurity. 

Designed specifically for beginners and those who are interested in a Cybersecurity Specialist or Analyst roles as well as entry-level roles in Information Security (Infosec) engineering. This course dives into the world of cybersecurity to give you the critical skills employers need. It also supports the needs of technical and IT support roles, who can find themselves on the front lines of defense for cybersecurity issues.

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IBM AI Engineering Professional Certificate

 

What you'll learn

Describe machine learning, deep learning, neural networks, and ML algorithms like classification, regression, clustering, and dimensional reduction 

Implement supervised and unsupervised machine learning models using SciPy and ScikitLearn 

Deploy machine learning algorithms and pipelines on Apache Spark 

Build deep learning models and neural networks using Keras, PyTorch, and TensorFlow 

Join Free:IBM AI Engineering Professional Certificate

Professional Certificate - 6 course series

Artificial intelligence (AI) is revolutionizing entire industries, changing the way companies across sectors leverage data to make decisions. To stay competitive, organizations need qualified AI engineers who use cutting-edge methods like machine learning algorithms and deep learning neural networks to provide data driven actionable intelligence for their businesses. This 6-course Professional Certificate is designed to equip you with the tools you need to succeed in your career as an AI or ML engineer.  

You’ll master fundamental concepts of machine learning and deep learning, including supervised and unsupervised learning, using programming languages like Python. You’ll apply popular machine learning and deep learning libraries such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow to industry problems involving object recognition, computer vision, image and video processing, text analytics, natural language processing (NLP), recommender systems, and other types of classifiers.

Through hands-on projects, you’ll gain essential data science skills scaling machine learning algorithms on big data using Apache Spark. You’ll build, train, and deploy different types of deep architectures, including convolutional neural networks, recurrent networks, and autoencoders.

In addition to earning a Professional Certificate from Coursera, you will also receive a digital badge from IBM recognizing your proficiency in AI engineering. 

Applied Learning Project

Throughout the program, you will build a portfolio of projects demonstrating your mastery of course topics. The hands-on projects will give you a practical working knowledge of Machine Learning libraries and Deep Learning frameworks such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow. You will also complete an in-depth Capstone Project, where you’ll apply your AI and Neural Network skills to a real-world challenge and demonstrate your ability to communicate project outcomes. 

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IBM Full Stack Software Developer Professional Certificate

 

What you'll learn

Master the most up-to-date practical skills and tools that full stack developers use in their daily roles

Learn how to deploy and scale applications using Cloud Native methodologies and tools such as Containers, Kubernetes, Microservices, and Serverless

Develop software with front-end development languages and tools such as HTML, CSS, JavaScript, React, and Bootstrap

Build your GitHub portfolio by applying your skills to multiple labs and hands-on projects, including a capstone

Professional Certificate - 12 course series

Prepare for a career in the high-growth field of software development. In this program, you’ll learn in-demand skills and tools used by professionals for front-end, back-end, and cloud native application development to get job-ready in less than 4 months, with no prior experience needed. 

Full stack refers to the end-to-end computer system application, including the front end and back end coding. This Professional Certificate covers development for both of these scenarios. Cloud native development refers to developing a program designed to work on cloud architecture. The flexibility and adaptability that full stack and cloud native developers provide make them highly sought after in this digital world. 

You’ll  learn how to build, deploy, test, run, and manage full stack cloud native applications. Technologies covered includes Cloud foundations, GitHub, Node.js, React, CI/CD, Containers, Docker, Kubernetes, OpenShift, Istio, Databases, NoSQL, Django ORM, Bootstrap, Application Security, Microservices, Serverless computing, and more. 

After completing the program you will have developed several applications using front-end and back-end technologies and deployed them on a cloud platform using Cloud Native methodologies. You will publish these projects through your GitHub repository to share your portfolio with your peers and prospective employers.

This program is ACE® recommended—when you complete, you can earn up to 18 college credits.

Applied Learning Project

Throughout the courses in the Professional Certificate, you will develop a portfolio of hands-on projects involving various popular technologies and programming languages in Full Stack Cloud Application Development. These projects include creating:

HTML pages on Cloud Object Storage

An interest rate calculator using HTML, CSS, and JavaScript

An AI program deployed on Cloud Foundry using DevOps principles and CI/CD toolchains with a NoSQL database

A Node.js back-end application and a React front-end application

A containerized guestbook app packaged with Docker deployed with Kubernetes and managed with OpenShift

A Python app bundled as a package

A database-powered application using Django ORM and Bootstrap

An app built using Microservices & Serverless

A scalable, Cloud Native Full Stack application using the technologies learned in previous courses

You will publish these projects through your GitHub repository to share your skills with your peers and prospective employers.

Join - IBM Full Stack Software Developer Professional Certificate

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