Why choose IBM Career Paths?
IBM Career paths have been designed based on relevant market research and valuable insights of industry experts. The curricula provides up to 50 hours of learning and is supposed to be done ideally on top of the regular academic program.
What we offer
Content currency
The content is provided by industry leader's, validated by educators and industry partners, and adopted by academic institutions globally.
Market Alignment
Our team has worked with industry experts to provide insights on careers that are taking over the job market. The course content is aligned to this market research, which is updated regularly to ensure our material stays relevant to the needs of the industry.
Open Badges
All career paths are comprised of globally recognized academic exams towards the end of the training. These exams are linked to an Open Badge, which our students or faculty can share to any of their social media accounts.
Career Offerings
The Big Data Engineer career path prepares students to use the Big Data platform and methodologies in order to collect and analyze large amounts of data from different sources. This will require skills in Big Data architecture, such as Apache Hadoop, Ambari, Spark, Big SQL, HDFS, YARN, MapReduce, ZooKeeper, Knox, Sqoop, and HBase.
Learning Modules
Module I - Big Data Overview
- Data Overview, Industry Applications, Case Studies
- Understanding Big Data
Module II - Big Data Engineer
- HortonWorks Data Platform
- Big Data architecture
- Storing and processing data with Hadoop
- Creating data using HDFS
- Data distribution and storage with MapReduce
- Access Hbase/Hadoop data with Hive
- ZooKeeper, Slider, Knox
- Loading data with Sqoop
- Big SQL
- IBM Watson Studio
IBM Open Badges
- Big Data Engineer 2018: Explorer | Mastery Award
Associated Job Roles
- Business Intelligence Analyst
- Artificial Intelligence Analyst
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The Business Intelligence Analyst career path prepares students to understand report building techniques using relational data models. They will also learn how to enhance, customize, and manage professional reports and will then further be explained about Active reports content and functionality.
Skills
Active Report Connections Active Report Variables Calculations Charts Conditional Formatting Crosstabs Decks Drill-Through Dynamic Reports Filters Formatting Reports HTML IBM Cognos Analytics Macros Multi-fact Query Prompts Queries Query Models Query Relationships RAVE Visualizations Report Bursting Reporting SQL Session Parameters Sorting Reports Visualizations
Market demand
Learning Modules
Module I - Analytics Overview
- Business Analytics Overview, Trends, Case Studies
- Understanding Business Intelligence and Analytics
Module II - Business Analytics Foundations
- Business Intelligence Overview
- Reports and Metadata models
Module III - Business Intelligence Analyst
- Introduction of Reporting Application
- List Reports and Crosstab Reports
- Data graphics (charts, numerals, visualization)
- Parameters and prompts
- Query models and relationships (using SQL)
- Advanced dynamic reports
- Data sorting using effective prompts
- Report distribution through Bursting
- Data user interaction with HTML
- Active Reports
IBM Open Badges
- Business Intelligence Analyst 2018: Explorer | Mastery Award
Associated Job Roles
- Predictive Analytics Modeler
- Data Scientist
- Data Engineer
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The Security Intelligence Engineer career path prepares students to consolidate event logs from device endpoints within a network to identify threats. This will require skills in security intelligence such as data security, event offenses, asset profile offenses and event rules. The Security Intelligence Engineer will use tools to investigate offenses that are generated from network logs and create rules that will prevent them from happening further.
Skills
Advanced Filtering Advanced Security Threats Asset Profiles Collecting Events Enterprise Security Architecture Event Offenses False Positives Host Definition Building Blocks Investigating Security Offenses Processing Events QRadar SIEM SIEM Reports Security Analyst Security Intelligence Security Offense Rules Security Offenses Security Vulnerabilities Threat Intelligence Feed Vulnerability Data
Market demand
Learning Modules
Module I - Cyber Security Overview
- Status quo of IT security
- Security Intelligence and operations
Module II - Security Intelligence Foundations
- Designing a Security Intelligence solution
- Security Intelligence functional components
Module III - Security Intelligence Engineer
- Collecting and processing events, flows, and vulnerability data
- Investigating an offense that is triggered by events
- Investigating the events of an offense
- Using asset profiles to investigate offenses
- Investigating an offense that is triggered by flows
- False positives overview
- Investigating superflows
- Using rules and building blocks
- Creating SIEM reports
- Performing advanced filtering
IBM Open Badges
- Security Intelligence Engineer 2017: Explorer | Mastery Award
Associated Job Roles
- Application Security Engineer
- Cloud Solution Administrator
- Predictive Analytics Modeler
- Watson Cognitive Specialist
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The Business Process Analyst career path prepares students to learn about managing upstream and downstream impacts and the cross-functional importance of processes to the overall objectives of an organization. It also explains important concepts such as process analysis, process improvement, macro design, Playback 0, and identifying and working with key performance indicators (KPIs).
Skills
BPM Analysis BPM Methodology Blueworks Live Business Process Management Business Process Model Business Strategy Flow Objects Hiring Requisition Key Performance Indicators Nested Process Notation Playback Zero Priority Matrix Process Optmizer Process Value Add Analysis Project Development To-be Analysis
Market demand
Learning Modules
Module I - Business Process Overview
- Business Process Overview, Trends, Case Studies
- Understanding the Business Process
Module II - Business Process Analyst Foundations
- Business Process Management (BPM) building blocks, organization and process
- The BPM lifecycle and components
- BPM essentials and value proposition
- BPM strategies
- IBM Business Process Manager features and components
Module III - Business Process Analyst
- BPM benefits to an organization
- Process modeling in BPM lifecycle
- Using Process Designer for process application, and structured and unstructured processes
- Playback 0 goals and requirements
- Macro design with Design Thinking
- Generating process diagram using Blueworks Live
- DevOps and its affect on development projects
- Key performance indicators (KPIs) for a process
- Steps in process improvement initiatives
IBM Open Badges
- Business Process Analyst 2017: Explorer | Mastery Award
Associated Job Roles
- Business Process Developer
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The Mobile Application Developer career path prepares students to develop native or hybrid mobile applications by using IDE, tools, or front-end framework, using IBM MobileFirst. This individual has demonstrated an understanding of how to use tools, such as Android SDK, Xcode and Cordova SDK, to create and publish mobile applications in public marketplaces and private enterprises.
Skills
Android SDK App Management App Monitoring App Publishing Application Application Center Authentication And Security Backend Integration CSS Client-side Logging Cloudant Command Line Interface Cordova Cross Platform Portability Deployment Development Kit Eclipse HTML5 Hybrid Coding JSONStore Java Adapters JavaScript JavaScript SQL Adapters Maven Mobile Application Developer Mobile Computing MobileFirst Operational Analytics Push Notification RESTful SDK Swift User Authentication Xcode iOS
Market demand
Learning Modules
Module I - Mobile Computing Overview
- Mobile Overview, Trends, Mobile Enterprise, Case Studies
- Understanding Mobile Computing
Module II - Mobile Application Foundations
- Roadmap to Mobile Web Development
- Introduction to HTML5 and JavaScript programming
- Developing Mobile Web applications with Dojo Mobile
- Developing Mobile Web applications with jQuery
Module III - Mobile Application Developer
- Mobile application design types
- Develop a mobile app to run on Android or iOS platforms
- Use client-side APIs for cross-platform portability
- Mobile Frameworks: Dojo and jQuery Mobile, Sencha Touch UI
- Use Apache Cordova framework to access native functions.
- Mobile Enterprise: Use IBM MobileFirst server-side APIs for back-end integration
- Secure a mobile application using authentication techniques.
- Manage updates and versions
IBM Open Badges
- Mobile Application Developer 2017: Explorer | Mastery Award
Associated Job Roles
- Mobile Application Administrator
- Cloud Application Developer
- Business Process Developer
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The Cloud Application Developer career path prepares students to develop, build, deploy, and test applications using a cloud platform to build Software as a Service (SaaS) solutions. This will require cloud application development skills, such as Node.js, REST architecture, JSON, Cloud Foundry and DevOps services. The Cloud Application Developer will use tools to build, deploy, run and manage applications on a cloud platform.
Skills
AngularJS Asynchronous I/O CSS Cloud Cloud Applications Cloud Computing Cloud Foundry Cloudant DB Cognitive Computing Command-line Interface DevOps Eclipse Eclipse Orion Express Framework Git GitHub HTML5 HTTP Server IBM Bluemix IBM Cloudant JAVA EE JSON Java Development Kit JavaScript Kinetise MBaaS Node.js Push Notification REST Architecture SDK Watson XML
Market demand
Learning Modules
Module I - Cloud Application Foundations
- Understanding Cloud Computing technologies
- Introduction to HTML5 and JavaScript programming
Module II - Cloud Application Developer
- Cloud Service models (IaaS, PaaS, SaaS)
- Bluemix applications
- Building applications using Node.js, Eclipse, Cloud Foundry and
- DevOps Services
- REST architecture, JSON and Functional security
- Data Services in Bluemix
- Server side JavaScript
- Web Application framework
IBM Open Badges
- Cloud Application Developer 2017: Explorer | Mastery Award
Associated Job Roles
- Cloud Solution Administrator
- Mobile Application Developer
- Mobile Application Administrator
- Business Process Developer
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The Artificial Intelligence career path prepares students to apply AI in real-life. This will require skills in machine learning, natural language processing (NLP), chatbots, and computer vision. Training topics will include AI, IBM Watson, hands-on and case studies on machine learning, NLP, chatbots, and computer vsion.
Skills
Algorithms Artificial Intelligence Business Analytics Chatbots Cognitive Computing Computer Vision Conversation CRISP-DM Discovery Evaluation Metrics IBM Watson Knowledge Studio Machine Learning Natural Language Processing Natural Language Understanding Notebooks Statistical Models Tone Analyzer Visual Recognition Watson Studio
Market demand
Learning Modules
Module I - Artificial Intelligence Overview
- AI overview, trends, advancements
- Types of AI, and its applications
- AI research focus
- Business analytics
Module II - Prerequisites
- IBM Watson and how it works
- Watson technology case studies
- From DeepQA to Watson services
- Watson services available on IBM Cloud
Module III - Artificial Intelligence Analyst
- Machine learning
- IBM Watson services, IBM Watson Studio,
- Watson Machine Learning, IBM Watson Knowledge Studio
- Deep learning and Neural Network Modeler
- NLP concepts, applications, and case studies
- NLP Watson services
- Introduction to chatbots and chatbots components
- How to build a chatbot with Watson Assistant
- Computer vision components and pipeline
- How to classify images with Watson Visual Recognition
- Building intelligent solutions by integrating Watson services
IBM Open Badges
- Artificial Intelligence Analyst: Explorer | Mastery Award
Associated Job Roles
- Cloud Application Developer
- Data Scientist
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The Predictive Analytics Modeler career path prepares students to learn the essential analytics models to collect and analyze data efficiently. This will require skills in predictive analytics models, such as data mining, data collection and integration, nodes, and statistical analysis. The Predictive Analytics Modeler will use tools for market research and data mining in order to predict problems and improve outcomes.
Skills
Automated Data Mining CLEM For Data Analytics Conversion Customer Segmentation Analytics Data Analysis Data Collection Data Integration Data Mining Data Modelling Data Plotting Data Preparation Data Relationships Data Stream Analytics Data Transformation Distribution Field Measurements Functions Histogram Configuration Matrics Means Modeling Nodes Predictive Analytics Modeler SPSS Modeler Storage String
Market demand
Learning Modules
Module I - Analytics Overview
- Business Analytics Overview, Trends, Case Studies
- Understanding Business Intelligence and Analytics
Module II - Business Analytics Foundations
- Introduction to Business Intelligence and Analytics
Module III - Predictive Analytics Modeler
- Data mining
- IBM SPSS Modeler, nodes, streams
- ACME data
- Deriving and reclassifying fields
- Modeling
- Data functions: date, conversion, string, statistical, missing value
- Sequence data
- Sampling, partitioning, and balancing data
- IBM Watson Studio, IBM Watson Machine Learning
- Neural networks and deep learning
IBM Open Badges
- Predictive Analytics Modeler: Explorer | Mastery Award
Associated Job Roles
- Business Intelligence Analyst
- Artificial Intelligence Analyst
- Security Intelligence Engineer
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The Blockchain Hyperledger Developer career path introduces students to blockchain concepts such as business networks, participants, assets, and trusted transactions, using Hyperledger Composer & Fabric, and IBM Blockchain Platform. This will require skills in topics such as shared ledger, smart contracts, consensus, and architecture of blockchain solutions.
Skills
Bitcoin Blockchain Blockchain Solution Architecture Business Network Chaincode Development Channels Consensus Docker Endorsement Policies Hyperledger Composer Hyperledger Fabric IBM Blockchain IBM Blockchain Platform IBM Cloud Integration With External Systems Kubernetes Ledger Peer And Orderer Nodes
Market demand
Learning Modules
Module I - Blockchain Overview
- Blockchain overview, business requirements, case studies.
Module II - Prerequisites
- Introduction to HTML5 and JavaScript Programming
- NodeJS, Server-side JavaScript, callback functions
- Docker Essentials, Containers Orchestration
- Getting Started with Kubernestese
Module III - Blockchain Developer
- Blockchain principles and its use in the enterprise
- Blockchain infrastructure and applications
- Identify participants, assets, transactions in a business network
- Public and permissioned blockchains
- Hyperledger Composer
- Blockchain solution architecture
- Peers, smart contracts, channels, world-state
- Consensus, ordering service, and transaction endorsement
- Hyperledger Fabric Application Development
- Chaincode structure, lifecycle and deployment approaches
- Blockchain deployment with Docker and Kubernetese
- Blockchain security on Hyperledger Fabric and Composer
- Blockchain integration with SDKs, APIs, IOT, and Cloud
IBM Open Badges
- Blockchain Developer 2018: Explorer | Mastery Award
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This IBM Mainframe Foundations career path is designed to give new hire IT professionals an introduction into the IBM Z environment. The IBM mainframe servers, operating systems and software products will be discussed. Through lectures and hands-on labs, this course will provide the basic skills to jump start productivity for technical professionals and undergraduate students of Information Technology university programs who are new to the mainframe environment.
Skills
Application Infrastructure Hardware Management Console (HMC) And Support Element (SE) IBM Developer For Z IBM Z Hardware IBM Z Software I/O Configuration Data Set (IOCDS) ISPF Editor JCL JES LPARs SPF/PDF TSO/E Commands TSO ISPF Panels Unix System Services Utilities And Conditional Execution z/OS Explorer z/OSMF z/OS Security
Market demand
Learning Modules
Module I - Mainframe Overview
- Mainframe history and characteristics
- Value of mainframes
- Operating systems and middleware for mainframes
Module II - Prerequisites
- Introduction to IBM Z environment
- z/OS security
- Time Sharing Option Extensions (TSO/E)
- Job Control Language (JCL)
- Job Entry Subsystem (JES)
- Unix System Services
Module III - Mainframe Foundations
- Why IBM Z?
- Features of IBM Z, hardware and software
- Hardware Management Console (HMC)
- Support Element (SE)
- Application infrastructure
- I/O configuration data set (IOCDS)
- Attributes of TSO/E and ISPF
- IBM z/OS Management Facility (z/OSMF)
- Security in the IBM Z environment
IBM Open Badges
- Mainframe Foundations 2018: Explorer | Mastery Award
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The IoT Cloud Developer career path prepares students to apply IoT and cloud computing concepts to build solutions based on devices connected to a cloud-based IoT platform. It explains the basic concepts of IoT, device connectivity protocols, data generated by sensors and other devices, cloud computing, device simulators, flow-based programming tools, REST APIs, and analytics. The concepts are then applied to practical use cases by using IBM Watson IoT Platform, Watson AI services, and tools on IBM Cloud.
Skills
Cloud Cloudant DB HTTP IBM Cloudant Internet Of Things MQTT Node-RED REST API Visual Recognition Watson Watson AI Watson IoT Platform
Market demand
Learning Modules
Module I - IoT Overview
- IoT overview
- IoT and its industry applications
Module II - IoT Foundations
- Node - RED
- REST API
- Build Node - RED application
- Cognitive web pages and messenger bot
Module III - IoT Cloud Developer
- Introduction to IoT
- IoT reference architecture
- IBM Watson IoT platform
- Connecting devices to the Watson IoT Platform
- Communication protocols used in IoT solutions
- Introduction to flow - based programming and Node - RED
- Manage devices and user access on Watson IoT Platform
- Applications and setting up security policies on Watson IoT Platform
- OSI & TCP/IP reference models
- MQTT & HTTP protocols
- Enhancing IoT solutions with REST APIs
- IBM Geospatial Analytics as a use case of IBM Streaming Analytics
- Analytics services of IBM Cloud
- IBM Cloud Object Storage
IBM Open Badges
- IoT Cloud Developer: Explorer | Mastery Award
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The Application Security Engineer career path prepares students to scan web applications against vulnerabilities and attacks. This will require skills in web application security such as scanning, and testing application in order to identify and analyze security vulnerabilities. Training topics will include OWASP security standards, Glassbox scanning, cross-site scripting, broken authentication, cross-site request forgery and threat analysis and reports.
Skills
AJAX AXF Application Scans Broken Authentication Cross-site Request Forgery Cross-site Scripting Ethical Hacking Function-level Access Control Glass Box HTML HTTP IBM AppScan Standard Injection Flaws Insecure Direct Object Reference OWASP Classifications SDK SDLC SQL Injection Scripting Security Breach Security Misconfiguration Security Scans Security Testing Security Vulnerabilities Sensitive Data Exposure Session Hijacking Threat Modeling Unvalidated Redirects Vulnerability Testing WASC Classification Web Application Security Web Services Web2.0
Market demand
Learning Modules
Module I - Cyber Security Overview
- Security Overview, Trends, Case Studies
- Security standards and frameworks
Module II - Cyber Security Foundations
- Application Security Technologies:
- HTML5 and JavaScript programming
- SQL relational database, objects and tables
Module III - Application Security Engineer
- Web application components and security issues
- OWASP web application security attack classifications
- SQL injection
- Brute force authentication
- Cross-site scripting (XSS)
- Insecure direct object reference
- Security misconfiguration
- Sensitive data exposure
- Cross-site request forgery (CSRF)
- Vulnerability testing, scanning and threat modeling
- Reporting threats and vulnerabilities
- Glass Box testing
- Scanning Web Services
- Extend functions by using SDK and AXF
- Troubleshooting IBM AppScan
IBM Open Badges
- Application Security Engineer 2017: Explorer | Mastery Award
Associated Job Roles
- Security Intelligence Engineer
- Mobile Application Developer
- Cloud Application Developer