Course
Building Marketing Workflows with n8n
- BasicSkill Level
- 4.8+
- 107 reviews
Build marketing workflows in n8n using AI agents. Automate campaign strategy, conversion optimization, and lead generation from scratch.
Artificial Intelligence
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
or
Course
Build marketing workflows in n8n using AI agents. Automate campaign strategy, conversion optimization, and lead generation from scratch.
Artificial Intelligence
Course
Learn to build and customize Sigma charts to tell clear, compelling data stories—no coding required.
Data Visualization
Course
Learn about the difference between batching and streaming, scaling streaming systems, and real-world applications.
Data Engineering
Course
Get to know the Google Cloud Platform (GCP) with this course on storage, data handling, and business modernization using GCP.
Cloud
Course
Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.
Data Preparation
Course
Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.
Artificial Intelligence
Course
Test a chatbot that matches customers with ideal skincare products using your prompting skills for personalized results.
Artificial Intelligence
Course
Learn the data engineering role on Google Cloud. Explore data sources, storage solutions, ETL/ELT architectures, BigQuery, Dataform, and Dataproc.
Cloud
Course
Stop rewriting the same joins and calculations, and dive into well-governed, scalable analytics using Sigma data models.
Reporting
Course
Build custom business apps without code using Microsoft Power Apps - from blank canvas to published, responsive app.
Artificial Intelligence
Course
Build dynamic Sigma calculations to explore data, automate logic, and uncover trends with practical business examples.
Data Manipulation
Course
Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.
Probability & Statistics
Course
Build interactive AI apps in Sigma using user input, actions, and polished interfaces, no coding required.
Reporting
Course
This course introduces Google Clouds AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects.
Cloud
Course
Learn how to set up and manage your Microsoft Fabric infrastructure.
Other
Course
Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.
Data Literacy
Course
In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.
Data Visualization
Course
Exploring Data Transformation with Google Cloud
Cloud
Course
Learn the basics of cash flow valuation, work with human mortality data and build life insurance products in R.
Applied Finance
Course
Learn how computers work, design efficient algorithms, and explore computational theory to solve real-world problems.
Software Development
Course
Explore Alteryx Designer in a retail data case study to boost sales analysis and strategic decision-making.
Data Preparation
Course
Interact with a customized GPT and use your prompting skills to plan and open your restaurant.
Artificial Intelligence
Course
Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.
Reporting
Course
This is an introductory level course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods.
Cloud
Course
Discover how to analyze and visualize baseball data using Power BI. Create scatter plots, tornado charts, and gauges to bring baseball insights alive.
Data Visualization
Course
Build a Databricks Genie space end-to-end: descriptions, synonyms, instructions, table relationships, example queries, monitoring, and benchmarks.
Data Engineering
Course
Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.
Reporting
Course
Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.
Software Development
Course
Trust and Security with Google Cloud
Cloud
Course
Connect data sources to your app to build a search and analysis engine. Master capabilities like deep research agents, ideation, and NotebookLM for analysis.
Cloud
Data science is an area of expertise focused on gaining information from data. Using programming skills, scientific methods, algorithms, and more, data scientists analyze data to form actionable insights.
You’ll need to learn a programming language such as Python or R and master the principles of math and statistics. Knowledge of data analysis methods and data science tools is also essential. There are many ways to learn data science. As well as formal means of education, such as a degree or university study, there are plenty of other resources to help you learn at your own pace. As well as online courses and tutorials, there are books, videos, and more.
As well as knowledge of mathematics and statistics, data scientists need programming skills in languages such as Python, R, and SQL. Additionally, data science requires the ability to work with large data sets, knowledge of data visualization, data wrangling, and database management. Skills in machine learning and deep learning can also be useful.
In a professional capacity, almost every industry can use data science to some degree. Healthcare organizations use data science to detect and cure diseases, while finance companies use it to detect and prevent fraud. All kinds of industries use data science for marketing, such as building recommendation systems and analyzing customer churn.
Yes, data science is among the fastest-growing sectors in the US and worldwide. It’s also one of the best-paid careers out there. According to data from Payscale, experience data scientists earn an average of $97,609 and have a satisfaction rating of four stars out of five in the US.
There are a few things to consider here. First, data science degrees can be competitive to get onto, often requiring consistently high grades. Similarly, many of the skills required for data science require a lot of study and patience. It can take several months to master all of the necessary basics, as well as a lot of practical experience to secure an entry-level position.
Yes, you’ll need some coding experience in languages such as Python, R, SQL, Java, and C/C++. However, due to its relatively simple syntax, Python programming language is often the preferred choice among newcomers.
For a person with no prior coding experience and/or mathematical background, it can typically take 7 to 12 months of intensive studies to be at the level of an entry-level data scientist. However, it is important to remember that learning only the theoretical basis of data science may not make you a real data scientist.
Once you’ve mastered the foundations of data science, you can then specialize in a variety of areas, including machine learning, artificial intelligence, big data analysis, business analytics and intelligence, data mining, and more.
Make progress on the go with our mobile courses and daily 5-minute coding challenges.