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You don't have to lose your job to a machine learning AI. Explore machine learning courses that can help you build the machine learning skills you need to launch or advance your career.
An April 2025 Forbes report highlights companies' willingness to replace human workers with AI. Many AI programs that might impact jobs use the latest machine learning advances. These advances let AI create customized responses and complete many routine tasks.
But machine learning doesn't need to put your career aspirations at risk. Dive into programs that can help you master machine learning and stand out in your current role or on the job market.
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What will you learn in a machine learning program?
Introductory machine learning courses can teach you the difference between AI and machine learning. Understanding how these AI-related fields of study compare can help you decide which to pursue.
Machine learning courses may emphasize relevant programming languages, such as Python. With Python, you can analyze linear models and neural networks, choose the best models for the applications, and run a project from start to finish. Consider taking an introduction to Python course before starting on machine learning.
Machine learning (ML)
Machine learning is a branch of artificial intelligence concentrated on developing computer systems that can learn independently. Machine learning programs can produce content that meets users' needs by analyzing large datasets.
Artificial intelligence (AI)
Artificial intelligence is a branch of computer science that creates computer systems that mimic or exceed human intelligence. Many consumer electronics contain primitive AI that can help people with simple tasks.
How to get started in machine learning
1. Shift your mindset to work with machine learning
Shifting your mindset to work with machine learning is an essential first step, especially considering its potential to upend the workforce. If you view machine learning as a thought partner rather than a rival, you can explore how this emerging technology can benefit you.
Before starting a course, experiment with popular machine learning programs like ChatGPT. Analyzing its responses can teach you about the technology's benefits and drawbacks. Reflect on these insights before continuing your journey.
2. Pick a problem to solve
After completing at least one machine learning course, consider how machine learning can solve a problem in your professional or personal life.
In the workplace, machine learning can help you with routine tasks, such as organizing data on a spreadsheet or identifying potential customers.
You want to pick a problem that matches your current ability level with machine learning.
As you dive in, don't become discouraged if you feel overwhelmed or you don't get the results you want on the first try. Learning anything new takes time. You may need further practice with machine learning tools.
3. Experiment with machine learning tools
Machine learning tools can make your educational journey much simpler. Explore popular tools that can help you master machine learning fundamentals and intermediate concepts. Prices are current as of June 2025.
- IBM Watson: With IBM Watson, you can analyze data, create machine learning software with natural language processing, and use applications to custom-tailor programs to your industry. Although you can try out IBM Watson for free, the plus plan featuring generative AI capabilities costs $140 per month.
- Microsoft Azure: Microsoft Azure can help you train and deploy AI models. Other benefits include support for different programming languages and scalable cloud storage. Azure Machine Learning costs $70-$2,242 per month, depending on the plan.
- TensorFlow: An open-source alternative to Microsoft Azure and IBM Watson, TensorFlow offers an extensive software library and support documentation. TensorFlow does not charge a subscription fee, making it a great option for budget-conscious learners.
4. Build a portfolio
Intermediate and advanced machine learning courses can help you build an online professional portfolio. Showcase projects highlighting your analytical skills and accomplishments. Add relevant commentary to each entry so hiring managers without a computer science background can understand your work.
Make sure to include a link to your portfolio on your résumé and practice discussing its content before job interviews.
How to choose the right machine learning program for you
- Current skill level: You can begin your career journey by considering your current skill level. Explore introductory courses if you lack a computer science or STEM background.
- Cost: You want to avoid debt as much as possible. Focus on free or low-cost introductory courses to learn the basics before committing to costlier certificate or degree programs.
- Timeline: Machine learning programs can take a few weeks to a few years. Calculate how long you need to reach your goals by determining how many hours you can commit to your education each week.
- Career goals: Decide whether you want to learn machine learning to protect your current job or advance your career. The former may require only a certificate, while the latter may require a degree.
- Program outcomes: Review program outcomes closely when comparing courses of study. Good programs prepare students for career advancement or a new job.
Courses
A machine learning course takes 4-12 weeks. Courses can help you learn specific knowledge and skills. Prices range from $50-$300.
Certificates
Consider a machine learning certificate if you want to improve your résumé and require a flexible learning format. A typical certificate takes 2-10 months and costs $500-$1,500.
Executive education
Machine learning executive education programs appeal to experienced professionals who want to learn in-demand skills. Programs cost $2,500-$3,500 and take 6-8 weeks.
Degrees
A bachelor's degree can help you develop foundational knowledge and prepare for a new career. A bachelor's takes 4-6 years to earn and costs $10,000-$200,000. A master's degree program costs about the same and requires 12-36 months to complete.
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Last updated July 2, 2025