Course
Querying a PostgreSQL Database in Java
- AdvancedSkill Level
- 4.7+
- 119 reviews
Connect Java to PostgreSQL with JDBC. Write secure queries, manage transactions, and handle large datasets efficiently.
Software Development
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
or
Course
Connect Java to PostgreSQL with JDBC. Write secure queries, manage transactions, and handle large datasets efficiently.
Software Development
Course
Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.
Machine Learning
Course
Build generative AI apps on Snowflake with Cortex LLM functions, prompt engineering, and fine-tuning.
Artificial Intelligence
Course
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.
Probability & Statistics
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
Course
Learn to import, manipulate, and transform data in Java using the Tablesaw library. Work with CSV files, tabular structures, and complex JSON formats.
Software Development
Course
Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.
Data Literacy
Course
Learn to use Amazon Bedrock to access foundation AI models and build with AI - without managing complex infrastructure.
Artificial Intelligence
Course
Learn to choose, build with, and secure AWS data stores including DynamoDB and S3 through hands-on console exercises and real-world scenarios.
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
Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.
Data Manipulation
Course
Learn how to reduce training times for large language models with Accelerator and Trainer for distributed training
Artificial Intelligence
Course
Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.
Data Preparation
Course
Learn to design scalable event-driven architectures in Azure using messaging services and real-world integrations.
Cloud
Course
In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.
Data Visualization
Course
Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.
Probability & Statistics
Course
Learn how to pull character strings apart, put them back together and use the stringr package.
Software Development
Course
Master data cleaning in Java using statistical methods, transformations, and validation for reliable apps.
Importing & Cleaning Data
Course
Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.
Software Development
Course
Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.
Reporting
Course
Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.
Importing & Cleaning Data
Course
This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.
Data Visualization
Course
This Power BI case study follows a real-world business use case where you will apply the concepts of ETL and visualization.
Data Visualization
Course
Build reliable Snowflake pipelines with DevOps and observability: Git, CI/CD, and Snowflake Trail monitoring.
Data Engineering
Course
Learn how to monitor, diagnose, and optimize Azure applications using Azure Monitor, Application Insights, and Log Analytics.
Cloud
Course
Learn how to load, transform, and transcribe speech from raw audio files in Python.
Data Manipulation
Course
Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.
Machine Learning
Course
Use your knowledge of common spreadsheet functions and techniques to explore Python!
Software Development
Course
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.
Probability & Statistics
Course
Learn survey design using common design structures followed by visualizing and analyzing survey results.
Probability & Statistics
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.