Top 3 Free Artificial Intelligence and Machine Learning Courses (2023)
Important Note About Artificial Intelligence and Machine Learning Courses
Before we dive into the Top 3 Free Artificial Intelligence and Machine Learning Courses (2023), it is vital to understand the relevance and future of these fields today and future too. AI and ML are transforming industries’ operations, from technology to healthcare, finance, marketing, and marketing.
Training in AI and AA is no longer an option but is necessary for those who want to keep up with technology trends. Here are three of the best free courses to help you start or advance your career in AI and AA.
Machine Learning and Artificial Intelligence
AI is a field of computer science that attempts to simulate and make artificial intelligence to enhance human and artificial intelligence together. On the other elements of ai hand, AA is a subsection of AI that focuses on developing algorithms that take over natural language understanding and allow computers to learn from data.
AI and AA courses should provide a solid foundation in artificial intelligence and deep learning in these two interrelated fields. Students should learn to understand and apply the principles and practices of AI and AA, and courses should equip students with the practical skills needed to apply these principles in real-world situations.
The Google AI Certification Courses
The Google AI Certification Course, specifically the Professional Machine Learning Engineer Certification, is designed to equip students with the skills to design, build, and produce Machine Learning (ML) models to solve business challenges using Google Cloud technologies. A professional in this field should be proficient in all aspects of model architecture, data pipeline interaction, and metrics interpretation and have a solid understanding of application development, infrastructure management, and data science and engineering, and data science governance. The course is keen on responsible AI throughout the ML software development process and encourages collaboration with other job roles for the long-term success of models.
The certification exam assesses the abilities of as data scientist to frame ML problems, mine key data and complex problems, develop ML models, architect ML solutions, automate and orchestrate ML pipelines, design data preparation and processing systems, and monitor, optimize, and maintain ML solutions.
The certification exam lasts two hours and costs $200 plus applicable taxes. It is conducted in English and consists of 50-60 multiple-choice and multiple-select questions. The exam can be taken either online or at a testing center. There are no prerequisites for the exam, but it is recommended that candidates have 3+ years of industry experience, including one or more years designing and managing solutions using Google Cloud. All Google Cloud certifications are valid for two years from the certificate date, and recertification is required to maintain the certification status.
In preparation for the Machine Learning Engineer exam, it is recommended that candidates have 3+ years of hands-on experience with Google Cloud products and solutions. The exam guide provides a complete list of topics that may be included in the exam. To prepare, candidates are encouraged to review the sample questions to familiarize themselves with the format and potential content. Various training resources are available to candidates, including online training, in-person classes, hands-on labs, and other resources from Google Cloud. Candidates can also get valuable exam tips, tricks, and industry experts’ insights. Once ready, candidates can schedule the exam and choose whether to take it remotely or at a nearby testing center.
This course provides a comprehensive and practical introduction to AI, covering key concepts in machine learning, such as supervised and unsupervised, machine learning itself, deep AI, and neural networks. It also offers opportunities to work on real-world projects, enabling students to apply what they’ve learned in the course in a practical context.
Want to learn how to build AI? Then do this
If you want to learn basic concepts about building AI systems, then Google’s course is an excellent choice. But beyond that free course, there are two other courses worth mentioning.
Google Machine Language Course
Firstly, Google provides a Machine Learning Crash Course that is an excellent entry point for those who want to learn about AI. This course offers a hands-on, practical introduction to machine learning using TensorFlow APIs. It is designed in a fast-paced manner and features a series of lessons, video lectures, real-world case studies, and practice exercises. The course is designed to take approximately 15 hours to complete and includes over 25 classes and 30 activities. Topics covered include key machine learning concepts like the differences between machine learning and traditional programming, understanding and measuring loss, gradient descent, model effectiveness, data representation, and building deep neural networks.
The Stanford University AI Course
Stanford University offers a free online course, “CS230: Deep Learning.” This course dives deep into the fundamentals of advanced machine learning and AI. The system consists of a series of lectures on topics such as deep learning intuition, full-cycle deep learning projects, adversarial attacks, AI in healthcare, deep learning project strategy, interpretability of neural networks, career advice, deep reinforcement, machine learning itself, and chatbots. The course videos are freely available online. Unfortunately, I couldn’t find details on the exact structure and content of the course within the allotted time.
Want to use AI for real-world business challenges? Then do this
Google also offers a Professional Machine Learning Engineer Certification for those looking to apply AI to real-world business challenges. This certification assesses your ability to frame ML problems, develop ML models, architect ML solutions, automate and orchestrate ML pipelines, design data preparation, and processing systems, and monitor, optimize, and maintain ML solutions. Google recommends having 3+ years of hands-on experience with Google Cloud products and solutions before attempting the Machine Learning Engineer exam. The certification process involves preparing for the exam, understanding the content, reviewing sample questions, training, and scheduling the exam.
Google Career Certificates for 2023:
1. Google IT Support Professional Certificate
– It’s the most popular Google career certificate and prepares students to enter the IT industry as support specialists.
– It includes five online courses, and it takes, on average, six months to complete.
– Courses cover technical support fundamentals, computer networking, operating systems, system administration, and IT security.
– Jobs you can apply for after completing this certificate include IT support specialist, junior system administrator, or system analyst.
– The starting salary for an entry-level IT support specialist in the US is around $50,000 annually. Professionals with more experience (10+ years) can become senior IT specialists and earn a salary of $69K per year.
2. Google UX Design Professional Certificate
– This certificate prepares students for a career in web and application design.
– It includes seven online courses and takes an average of 4 months to complete.
– Courses cover topics like foundations of UX design, building wireframes, performing UX research, creating websites, and mobile app prototypes.
– Jobs you can apply for after completing this certificate include UX designer, web designer, application designer, or web developer.
– The average salary for entry-level UX-design jobs is $58,600 per year and can rise to $108K per year for the more experienced (10+ years).
3. Google IT Automation Professional Certificate
– It is the most popular programming certification offered by Google and teaches students how to create computer programs and automate everyday tasks using Python.
– It includes six online courses and takes an average of 4 months to complete.
– Courses cover topics related to computer programming, including how to use Python to create programs and scripts, how to use Git and GitHub to store and distribute your software, and how to write efficient computer code.
– Jobs you can apply for after completing this certificate include Python programmers either in a company’s IT department or as freelance developers.
4. Google Data Analytics Professional Certificate
– This is one of the most valuable Google career certifications you can get.
– Certified data analysts get an entry-level salary of $67,900 annually and can grow to more than $110K once they get 10+ years of working experience.
– The certificate includes eight online courses, and it takes at least eight months to complete all lessons.
– Courses cover topics related to data management, including data processing, data visualization, and data analysis.
– It is suitable for people who like working with data, numbers, spreadsheets, and making presentations【34†source】.
5. Google Project Management Professional Certificate
– This certificate is the best to pursue if you want to start a project management career.
– It’s an entry-level certification that can get you a job as a project manager and prepare you to obtain the PMP certification, the industry standard in project management.
– The average salary for entry-level project managers is $59,000 per year. Experienced project managers handling big projects can quickly get a minimum of $100K annually.
Many other Google career certificates are available, including Google Digital Marketing & eCommerce Professional Certificate, Google Advanced Data Analytics Professional Certificate, Google Business Intelligence Professional Certificate, and Google Cybersecurity Professional Certificate.
If you’re interested in a specific field, I’d recommend looking into the Google Career Certificate that aligns with your career goals.
