IBM Courses

Cybersecurity Job Search, Resume, and Interview Prep

136 ratings at Coursera

Prepare for entry-level cybersecurity roles: build an ATS-compatible resume, portfolio, cover letter, and elevator pitch, then practice STAR answers, technical screenings, and salary negotiation.

• Coursera
• 4 weeks, 3 hours a week
• Self-Paced
• Paid Course

IBM COBOL Basic Testing and Debugging

133 ratings at Coursera

Identify common COBOL run-time errors and file status codes, apply compile options, mainframe unit testing and TDD, and debug programs with the IBM z/OS Debugger.

• Coursera
• 5 weeks, 2 hours a week
• Self-Paced
• Paid Course

AI Workflow: Data Analysis and Hypothesis Testing

129 ratings at Coursera

Perform exploratory data analysis for a hypothetical streaming media company: apply visualization best practices, handle missing data with imputation, estimate with probability distributions, and correct for multiple testing.

• Coursera
• 2 weeks, 5 hours a week
• Self-Paced
• Paid Course

Introduction to Program Management

127 ratings at Coursera

Learn to define programs, work through the program management lifecycle, run a PMO, manage stakeholders with RACI charts, and weigh PMI-PgMP certification and career paths.

• Coursera
• 3 weeks, 2 hours a week
• Self-Paced
• Paid Course

Project Management Capstone

122 ratings at Coursera

Manage a project end to end: build a charter, work breakdown structure, network diagram, budget, risk register, user stories, sprint backlog, Kanban board, and closeout report.

• Coursera
• 5 weeks, 4 hours a week
• Self-Paced
• Paid Course

Project Management Job Search, Resume, and Interview Prep

119 ratings at Coursera

Prepare for a project management job hunt: build a portfolio and elevator pitch, write ATS-friendly resumes and cover letters, and answer behavioral questions with the STAR technique.

• Coursera
• 5 weeks, 3 hours a week
• Self-Paced
• Paid Course

Generative AI Engineering and Fine-Tuning Transformers

119 ratings at Coursera

Fine-tune large language models with Hugging Face and PyTorch: load and pretrain transformers, then apply PEFT, adapters, LoRA, QLoRA, quantization, and soft prompts.

• Coursera
• 2 weeks, 4 hours a week
• Self-Paced
• Paid Course

Agentic AI with LangChain and LangGraph

117 ratings at Coursera

Build agentic AI systems in LangGraph: design stateful workflows with memory and conditional logic, implement Reflection, Reflexion and ReAct agents, and coordinate multi-agent RAG.

• Coursera
• 3 weeks, 4 hours a week
• Self-Paced
• Paid Course

Data Science with R - Capstone Project

116 ratings at Coursera

Play data scientist on a bike-sharing challenge: scrape web and API data, wrangle with Tidyverse, explore via SQL and ggplot2, fit regressions, ship a Shiny dashboard.

• Coursera
• 6 weeks, 4 hours a week
• Self-Paced
• Paid Course

Machine Learning with Apache Spark

116 ratings at Coursera

Build regression, classification, and clustering models with SparkML: connect to Spark clusters, run ETL and Structured Streaming jobs, and assemble machine learning pipelines.

• Coursera
• 4 weeks, 4 hours a week
• Self-Paced
• Paid Course

Agentic AI with LangChain and LangGraph

116 ratings at Coursera

Build stateful, self-improving agents with LangGraph: ReAct architectures, conditional execution, iterative refinement, multi-agent collaboration, and agentic RAG for context-aware question answering.

• Coursera
• 3 weeks, 4 hours a week
• Self-Paced
• Paid Course

Agentic AI with LangGraph, CrewAI, AutoGen and BeeAI

114 ratings at Coursera

Build multi-agent systems with LangGraph, CrewAI, BeeAI, and AG2 (AutoGen): apply routing and parallelization patterns, orchestrate agents and tools, and generate structured outputs with YAML and Pydantic.

• Coursera
• 3 weeks, 4 hours a week
• Self-Paced
• Paid Course

Monitoring and Observability for Development and DevOps

110 ratings at Coursera

Monitor application health with Prometheus, Grafana, Mezmo, and Instana: golden signals, alerting, log retention, distributed tracing, telemetry, and the three pillars of observability.

• Coursera
• 5 weeks, 3 hours a week
• Self-Paced
• Paid Course

Deep Learning with PyTorch

107 ratings at Coursera

Build and train neural networks in PyTorch: logistic and softmax regression, shallow and deep nets with dropout and batch norm, and CNNs with ResNet18 transfer learning.

• Coursera
• 6 weeks, 3 hours a week
• Self-Paced
• Paid Course

Data Engineering Career Guide and Interview Preparation

105 ratings at Coursera

Prepare for data engineer job hunting: understand the role, build a resume and portfolio, craft cover letters and an elevator pitch, research openings, and handle interviews and code challenges.

• Coursera
• 4 weeks, 3 hours a week
• Self-Paced
• Paid Course