
Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Model Optimization, Generative AI, Google Cloud Platform, Model Deployment, Tensorflow, Generative AI Agents, Google Gemini, Model Training, Dataflow, Big Data, Keras (Neural Network Library), Machine Learning, Generative Model Architectures, Data Preprocessing, Machine Learning Software, CI/CD, Model Evaluation, Cloud Computing
★ 4.4 (4.9K) · Intermediate · Professional Certificate · 3 - 6 Months

Skills you'll gain: Generative AI, Generative AI Agents, Google Gemini, Google Cloud Platform, Generative Model Architectures, MLOps (Machine Learning Operations), Prompt Engineering, Tensorflow, AI Workflows, Cloud Infrastructure, Applied Machine Learning, Artificial Intelligence, Data Infrastructure, Multimodal Prompts, Model Deployment, Model Training, Machine Learning, Model Evaluation, Supervised Learning
★ 4.6 (326) · Beginner · Course · 1 - 3 Months

Board Infinity
Skills you'll gain: Feature Engineering, Model Evaluation, Model Deployment, Fine-tuning, Data Preprocessing, Model Training, Deep Learning, Machine Learning Methods, Model Optimization, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Scalability, Hugging Face, Docker (Software), Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Application Deployment, Software Development, Machine Learning
Intermediate · Specialization · 1 - 3 Months

Google Cloud
Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Model Deployment, AI Orchestration, AI Workflows, Generative AI, Google Cloud Platform, Data Modeling, Continuous Monitoring, Data Pipelines, Model Training, Feature Engineering, Model Optimization, DevOps, Agentic Workflows, Generative AI Agents, Data Store, Continuous Deployment, Forecasting, Metadata Management
★ 4 (496) · Intermediate · Specialization · 3 - 6 Months

Google Cloud
Skills you'll gain: Feature Engineering, Model Optimization, Generative AI, Model Deployment, Tensorflow, Generative AI Agents, Google Gemini, Model Training, Keras (Neural Network Library), Machine Learning, Generative Model Architectures, Data Preprocessing, Machine Learning Software, MLOps (Machine Learning Operations), Google Cloud Platform, Model Evaluation, Applied Machine Learning, Data Cleansing, Data Quality, Cloud Computing
★ 4.4 (3.8K) · Intermediate · Specialization · 3 - 6 Months

Google Cloud
Skills you'll gain: Model Deployment, Model Optimization, Convolutional Neural Networks, Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Large Language Modeling, Reinforcement Learning, Model Training, Transfer Learning, Computer Vision, Keras (Neural Network Library), Systems Design, Applied Machine Learning, Image Analysis, AI Personalization, Cloud Deployment, Recurrent Neural Networks (RNNs), Machine Learning
★ 4.5 (1.5K) · Advanced · Specialization · 3 - 6 Months

Multiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Methods, Model Training, Applied Machine Learning, Machine Learning Algorithms, Transfer Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Model Evaluation, Responsible AI, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms
★ 4.9 (39K) · Beginner · Specialization · 1 - 3 Months

Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Machine Learning Methods, Model Training, Random Forest Algorithm, Model Optimization, Data Analysis, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms
★ 4.8 (617) · Advanced · Course · 1 - 3 Months

Skills you'll gain: Dashboard Creation, Model Deployment, Feature Engineering, PySpark, Data Import/Export, Big Data, Apache Spark, Apache Hadoop, Dashboard, Data Architecture, Data Governance, Apache Kafka, Data Store, Cloud Services, Cloud Deployment, Metadata Management, Data Storage, Data Quality, Data Cleansing, Machine Learning Methods
★ 4.6 (4.4K) · Intermediate · Specialization · 3 - 6 Months

DeepLearning.AI
Skills you'll gain: Supervised Learning, Applied Machine Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, Model Training, NumPy, Machine Learning Algorithms, Predictive Modeling, Classification Algorithms, Feature Engineering, Artificial Intelligence, Model Evaluation, Data Preprocessing, Python Programming, Logistic Regression, Model Optimization, Regression Analysis, Algorithms
★ 4.9 (32K) · Beginner · Course · 1 - 4 Weeks

Google Cloud
Skills you'll gain: Business Transformation, Innovation, Digital Transformation, Serverless Computing, Cloud Services, Data Ethics, Cloud Infrastructure, Google Cloud Platform, Culture Transformation, Application Programming Interface (API), Technology Strategies, Cloud Security, Data Mapping, Applied Machine Learning, Hybrid Cloud Computing, Data Strategy, Model Training, Cloud Platforms, Image Analysis, Infrastructure As A Service (IaaS)
★ 4.7 (7.6K) · Beginner · Specialization · 1 - 3 Months

Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Machine Learning Methods, Applied Machine Learning, Model Training, Statistical Machine Learning, Predictive Modeling, Machine Learning Algorithms, Machine Learning, Dimensionality Reduction, Decision Tree Learning, Python Programming, Logistic Regression, Model Optimization, Predictive Analytics, Classification Algorithms
★ 4.7 (18K) · Intermediate · Course · 1 - 3 Months
Google Machine Learning is a powerful tool developed by Google that uses artificial intelligence to create systems that can learn and improve from experience without being explicitly programmed. It focuses on developing computer programs that can access and use data to learn for themselves. This tool is used in various sectors of technology and business to analyze data and predict future trends. Someone interested in building Google Machine Learning skills must learn about algorithms, data analysis, programming, and statistics. ‎
Machine Learning Engineer: These individuals design, implement, and deploy scalable machine learning solutions using platforms like TensorFlow. They might work on anything from refining search algorithms to designing new recommendation systems.
Data Scientist: While closely related to ML engineers, data scientists often focus more on data exploration, hypothesis testing, and deriving insights from vast amounts of data. They might use Google's ML tools to analyze data and develop predictive models.
Research Scientist (AI/ML): Especially prevalent at Google, these roles focus on advancing the frontier of machine learning. They'll develop new algorithms, refine existing ones, and work on practical and theoretical challenges in the field.
ML Solutions Architect: These professionals might work with business stakeholders to design ML-based solutions for specific business problems, ensuring that the technical solution aligns with business goals.
Technical Program Manager (Machine Learning): They oversee ML projects, ensuring resources, timelines, and stakeholders are aligned. They also work to bridge the gap between technical and non-technical teams.
AI Product Manager: These individuals guide the strategy and development of AI-driven products, ensuring that they meet user needs while being technically feasible.
Cloud Engineer specializing in ML services: With Google Cloud offering specialized services for machine learning (like AI Platform), there's demand for cloud engineers who specialize in setting up, deploying, and managing ML services on the cloud.
To get started with Google Machine Learning on Coursera:
ML Foundations: Enroll in introductory machine learning courses on Coursera, focusing on core concepts and techniques. Google's Frameworks: Dive into courses that cover Google's ML tools, especially TensorFlow and Google Cloud ML Engine. Hands-on Learning: Choose courses that provide practical exercises utilizing Google's machine learning platforms and technologies. Earn Certifications: Complete course materials and assessments to obtain certificates, showcasing your proficiency in Google's ML ecosystem. ‎