SQL Classes Live Online: Best Remote/Virtual SQL Training

Learn More About Live Online SQL Courses

SQL is one of the most essential programming languages used by developers, data scientists, and data analysts. SQL stands for Structured Query Language and allows users to query, or extract data from databases. Users can quickly pull data from different tables, join tables, summarize data, and manage large data sets. Websites are connected to SQL databases on the back end, which allows the website to retrieve data. Whenever you search a website or pull up a list of transactions for your bank account, SQL queries are being run in the background to retrieve that information.

What Will I Learn in an SQL Class?

In an SQL (Structured Query Language) class, you will embark on a journey to master one of the most widely used languages for managing and querying data in relational database management systems (RDBMS). Here’s a condensed overview of what you can expect to learn in an SQL class:

Introduction to Databases and SQL: You’ll start by understanding the fundamental concepts of databases and their importance in modern applications. This includes an introduction to SQL and its role in data management, as well as an overview of relational database concepts such as tables, rows, columns, and relationships.

Basic SQL Commands: You’ll learn foundational SQL commands such as SELECT, INSERT, UPDATE, and DELETE for querying and manipulating data. These commands form the building blocks of SQL queries and allow you to interact with databases to retrieve, insert, update, and delete data.

Data Definition Language (DDL): You’ll explore DDL commands like CREATE, ALTER, and DROP for defining and modifying database objects such as tables, indexes, and views. This includes understanding data types and constraints used to define table structures and enforce data integrity.

Data Manipulation Language (DML): You’ll master DML commands like INSERT, UPDATE, and DELETE for modifying data within tables. This involves understanding transaction management and the use of COMMIT and ROLLBACK commands to control data charges.

Querying Data with SELECT Statement: A significant portion of the class will focus on the SELECT statement for retrieving data from one or multiple tables. You’ll learn about various clauses like WHERE, ORDER BY, GROUP BY, and HAVING for filtering, sorting, grouping, and aggregating data.

Joining Tables: You’ll delve into different types of joins (e.g., INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN) for combining data from multiple tables. This includes writing complex queries involving multiple tables using join operations.

Subqueries and Derived Tables: You’ll explore subqueries and their use in writing nested queries for advanced data retrieval. Additionally, you’ll learn about derived tables and their role in simplifying complex queries.

Functions and Aggregations: An important aspect of SQL is understanding functions for manipulating data (e.g., string functions, date functions, mathematical functions). You’ll also learn about aggregate functions (e.g., SUM, AVG, COUNT, MIN, MAX) for performing calculations on grouped data.

Views, Indexes, and Constraints: You’ll learn about creating and managing views for virtual representations of data, understanding indexes and their impact on database performance, and implementing constraints (e.g., PRIMARY KEY, FOREIGN KEY, UNIQUE) for ensuring data integrity.

Practical Application and Real-world Projects: Throughout the class, you’ll apply SQL skills to real-world scenarios and projects. This involves building databases, designing schemas, and writing complex queries to solve practical projects, providing you with hands-on experience.

In summary, an SQL class offers a comprehensive curriculum covering the essential aspects of SQL, from basic commands to advanced querying techniques, preparing you to effectively manage and manipulate data in relational databases.

How Long Will it Take to Learn SQL?

The time it takes to learn SQL (Structured Query Language) can vary significantly depending on several factors, including your prior experience with programming and databases, the complexity of the SQL concepts you want to learn, the resources available for learning, and your learning style and dedication. While it’s difficult to provide an exact timeframe, let’s break down some of the factors that may influence the learning process and provide a general guideline for how long it might take to become proficient in SQL.

Prior Experience: If you have prior experience with programming languages or databases, you may find it easier to grasp SQL concepts and syntax. Familiarity with concepts like data types, variables, and basic programming logic can accelerate your learning process. On the other hand, if you’re new to programming and databases, you may need to spend more time understanding fundamental concepts before diving into SQL.

Learning Resources: The availability of high-quality resources can significantly impact your learning speed. There are numerous online tutorials, courses, books, and interactive platforms dedicated to teaching SQL, ranging from beginner to advanced levels. Choosing well-structured and comprehensive learning materials that suit your learning style can expedite your progress.

Learning Style and Dedication: Your learning style and dedication play a crucial role in how quickly you can learn SQL. Some people prefer self-paced learning and can dedicate several hours each day to studying SQL, while others may prefer a more structured approach, such as attending classes or participating in guided online courses. Consistency and practice are key; dedicate regular time to study and practice SQL concepts will help you reinforce your learning and accelerate your progress.

Complexity of SQL Concepts: SQL encompasses a wide range of concepts, from basic commands for querying and manipulating data to more advanced topics like joins, subqueries, and database administration. The time it takes to learn SQL will depend on how deep you want to delve into these concepts. For example, if you’re primarily interested in basic querying and data manipulation, you may achieve proficiency in a relatively short amount of time. However, mastering more advanced topics may require additional time and effort.

Real-world Application: Applying SQL concepts to real-world projects and scenarios can significantly enhance your learning experience and help solidify your understanding SQL. Hands-on practice allows you to encounter common challenges and learn how to solve them using SQL. Engaging in practical projects, such as building databases, writing queries to retrieve specific information, and analyzing data, can accelerate your learning and provide valuable experience.

Given these factors, it’s difficult to provide a precise time frame for learning SQL. However for someone with no prior programming or database experience dedicating consistent time to learning SQL (e.g., several hours per week) and utilizing effective learning resources, it’s reasonable to expect to achieve basic proficiency within a few weeks to a couple months. With continued practice and exploration of more advanced topics, you can gradually enhance your SQL skills over time. Ultimately, the key to learning SQL, like any other skill, is dedication, practice, and a willingness to learn and adapt.

What Skills Should I Learn Alongside SQL?

Learning SQL opens up a wide range of opportunities in the field of data management and analysis. However, to enhance your proficiency and marketability, it’s beneficial to complement your SQL skills with additional tools, technologies, and soft skills that are highly relevant in today’s data-driven landscape. Here are some skills that you can learn alongside SQL to bolster your capabilities and advance your career:

Database Management Systems (DBMS): Understanding different database management systems, such as MySQL, PostgreSQL, SQL Server, Oracle, and NoSQL databases like MongoDB, will broaden your knowledge and enable you to work with diverse data platforms.

Data Visualization: Proficiency in data visualization tools and techniques such as Tableau, Power BI, or Python libraries like Matplotlib and Seaborn, allows you to create insightful visualizations that communicate complex data effectively.

Data Analysis: Learning data analysis skills using tools like Python’s pandas library or R programming language enables you to perform advanced data manipulation, exploration, and statistical analysis, enhancing your ability to derive meaningful insights from data.

Statistical Analysis: Familiarity with statistical concepts and methods, such as hypothesis testing, regression analysis, and machine learning algorithms, equips you with the knowledge to conduct in-depth data analysis and make data-driven decisions.

Programming Languages: Apart from SQL, learning programming languages like Python, R, or Java expands your technical skill set and enables you to automate tasks, build data-driven applications, and integrate SQL with other technologies.

ETL (Extract, Transform, Load): Understanding ETL processes and tools like Apache Spark, Talend, or Informatica enables you to extract data from various sources, transform it into a suitable format, and load it into a target database or data warehouse.

Cloud Computing: Familiarity with cloud platforms like AWS, Google Cloud Platform (GCP), or Microsoft Azure and services like Amazon Redshift, Google BigQuery, or Azure SQL Database allows you to deploy, manage, and scale databases and analytics solutions in the cloud.

Business Intelligence (BI) Tools: Proficiency in BI tools such as Microsoft Power BI, Tableau, or QlikView enables you to create interactive dashboards, reports, and data visualizations that facilitate data-driven decision-making within organizations.

Data Warehousing: Understanding concepts related to data warehousing, such as dimensional modeling, data mart design, and data warehouse architecture, prepares you to design and implement scalable and efficient data storage solutions.

Soft Skills: In addition to technical skills, cultivating soft skills like communication, problem-solving, critical thinking, and teamwork enhances your ability to collaborate effectively with colleagues, understand business requirements, and present insights derived from data in a compelling manner.

By acquiring these complementary skills alongside SQL, you can position yourself as a well-rounded data professional capable of handling diverse data challenges, driving insights, and contributing effectively to organizational success in today’s data-driven world. Continuously updating and expanding your skill set in line with evolving technologies and industry trends will further enhance your career prospects and enable you to stay competitive in the rapidly changing landscape of data management and analysis.

Is it Better to Learn SQL Virtually or Online?

Deciding whether it’s better to learn SQL virtually or in-person depends on various factors such as individual preferences, learning style, accessibility, and specific learning goals. Both methods offer unique advantages and considerations that can influence the learning experience and outcome.

In-person learning traditionally involves attending physical classes, workshops, or training sessions conducted in a classroom setting with an instructor and fellow students present. Here’s some factors to consider when evaluating in-person learning for SQL:

Advantages

Immediate Interaction: In-person classes provide direct interaction with instructors and peers, facilitating real-time feedback, clarification of concepts, and collaborative learning experiences.

Structured Environment: Classroom-based learning offers a structured environment with scheduled sessions, assignments, and assessments, providing a guided learning path and accountability.

Hands-on Experience: Some in-person classes may include hands-on exercises, practical labs, or group projects that allow students to apply SQL concepts in a real-world context.

Networking Opportunities: Physical classrooms provide opportunities for networking and forming connections with instructors, classmates, and industry professionals, which can be valuable for future collaborations or career advancement.

Considerations

Location and Accessibility: In-person classes may require commuting to a physical location, which can be challenging for individuals with limited access to transportation or living in remote areas.

Time Constraints: Scheduled classes may not always align with individual schedules, making it difficult for working professionals or individuals with other commitments to attend regularly.

Cost: In-person classes may involve additional costs such as tuition fees, transportation expenses, and materials, which can be prohibitive for some learners.

Limited Flexibility: Classroom-based learning typically follows a fixed schedule and pace, offering less flexibility compared to self-paced or learning options.

Virtual learning involves attending classes, workshops, or training sessions remotely via video conferencing platforms, virtual classrooms, or online learning platforms. There are some factors to consider when evaluating virtual learning for SQL:

Flexibility: Virtual classes offer flexibility in terms of scheduling, allowing students to attend sessions from anywhere with an internet connection and adapt the learning experience to their individual schedules.

Accessibility: Remote learning eliminates geographical barriers, providing access to high-quality instruction and resources for learners worldwide, regardless of their location.

Cost-effectiveness: Virtual classes may be more cost-effective than in-person alternatives, as they eliminate the need for commuting, accommodation, or other associated expenses.

Diverse Learning Resources: Virtual learning platforms often provide a wide range of resources such as recorded lectures, interactive tutorials, discussion forums, and supplementary materials, enriching the learning experience.

Considerations

Technical Requirements: Virtual learning requires reliable internet access, compatible devices, and familiarity with video conferencing tools, which may pose challenges for individuals with limited access to technology.

Potential for Distraction: Remote learning environments may present distractions such as home responsibilities, environmental factors, or digital distractions, impacting focus and productivity.

Limited Interaction: Virtual classes may lack the immediacy of in-person interaction, resulting in delayed feedback, limited opportunities for spontaneous discussion, and less personalized instruction.

Self Discipline: Virtual learning requires self-discipline and motivation to stay engaged with the course material, complete assignments, and maintain progress without direct supervision.

In summary, the choice between learning SQL virtually or in-person depends on individual preferences, circumstances, and learning goals. While in-person learning offers immediate interaction, a structured environment, and hands-on experience, virtual learning provides flexibility, accessibility, and cost-effectiveness. Ultimately, selecting the most appropriate learning method involves considering factors such as location, schedule, resources, and personal learning preferences to maximize the learning experience and achieve desired outcomes in acquiring SQL skills.

SQL Career Opportunities

SQL is a required skill in countless professions across data and development. In the data industry, Data Scientists, Data Analysts, Machine Learning Engineers, and others use SQL to extract data to analyze, make predictions, create algorithms, and more. In development, Web Developers and Software Engineers use SQL to pull data from databases to display on websites. SQL Developers develop databases for various business purposes as well as performing database maintenance and troubleshooting issues that may occur from bad or corrupt data. While SQL is an essential skill in many professions, most career paths requiring SQL would likely require additional skills, including Python, Git, HTML & CSS. Here’s some more information about jobs that use SQL:

Database Administrators are responsible for managing and maintaining databases to ensure their efficient and secure operation. They oversee the installation, configuration, and upgrading of database management systems (DBMS) such as MySQL, PostgreSQL, Oracle, SQL Server, and others, DBAs also monitor database performance, optimize query execution, and troubleshoot any issues that arise. SQL plays a crucial role in the work of a DBA as they use it to perform various tasks related to database management. They use SQL’s Data Definition Language (DDL) to design database schemas, create tables, define relationships between tables, and establish data integrity constraints.

Additionally, DBAs utilize SQL’s Data Manipulation Language (DML) to insert, update, delete, and query data in databases. They write SQL queries to retrieve specific information, modify existing data, or perform data analysis. Furthermore, DBAs rely on SQL to perform routine maintenance tasks such as indexing, backing up, restoring, and optimizing databases. They write SQL scripts to automate these tasks and ensure the smooth operation of databases. Overall, SQL is an essential tool for DBAs, enabling them to efficiently manage and manipulate databases to meet the needs of organizations and ensure data integrity and security.

Data Analysts are professionals who collect, process, and analyze data to extract valuable insights that can inform decision-making and drive business strategy. Their role involves working with large datasets from various sources, including databases, spreadsheets, and other data repositories. Data Analysts use statistical techniques, data mining, and machine learning algorithms to identify trends, patterns, and correlations within the data. One of the primary responsibilities of Data Analysts is to clean and preprocess data to ensure its accuracy and consistency.

This involves removing duplicates, handling missing values, and transforming data into a usable format for analysis. Once the data is prepared, data analysts use tools such as SQL, Python, R, and Excel to perform exploratory data analysis, generate descriptive statistics, and visualize fundings through charts, graphs, and dashboards. Data Analysts also collaborate with stakeholders across different departments to understand their data needs and develop analytical solutions to address specific business challenges. They communicate their findings and insights effectively through reports, presentations, and data storytelling, enabling decision-makers to make informed decisions based on data-driven insights. Overall, Data Analysts play a crucial role in transforming raw data into actionable insights that drive business growth and innovation.

Software Developers are professionals who design, develop, test and maintain software applications to meet the needs of users and organizations. Their role involves understanding user requirements, translating them into technical specifications, and building software solutions using programming languages and development tools. Software Developers work across various stages of the software development lifecycle. During the planning and design phase, they collaborate with stakeholders to gather requirements and create architectural designs for the software application. They use their expertise in programming languages such as Java, Python, C++, or JavaScript to write code that implements the desired functionality.

Once the code is written, Software Developers monitor its performance, address any issues that arise, and implement updates or enhancements as needed. They may also provide technical support to end-users and collaborate with other team members, such as Quality Assurance Testers and Product managers, to continuously improve the software. Overall, Software Developers play a crucial role in creating innovative software solutions that address the needs of users and contribute to the success of organizations in various industries.

Business Intelligence (BI) Analysts are professionals who use data analysis tools and techniques to gather, analyze, and interpret data from various sources within an organization. Their primary role is to provide valuable insights and actionable information to support strategic decision-making and improve business performance. BI Analysts work with large datasets, often stored in data warehouses or other centralized repositories, to extract meaningful insights that can help organizations understand market trends, customer behavior, and business performance metrics. They use data visualization tools such as Tableau, Power BI, or QlikView to reports, dashboards, interactive visualizations that communicate complex data findings in a clear and understandable manner.

In addition to data analysis and visualization, BI Analysts collaborate with stakeholders across different departments to understand their data needs and requirements. They gather and prioritize business requirements, identify key performance indicators (KPIs), and develop analytical solutions to address specific business challenges. BI Analysts also monitor and track the performance of key metrics over time, identify trends and patterns, and make recommendations for improvement based on data-driven insights. They play a crucial role in helping organizations make informed decisions, optimize business processes, and gain a competitive advantage in the marketplace.

Data Scientists are professionals who use their expertise in mathematics, statistics, programming, and domain specific knowledge to analyze large and complex datasets and extract valuable insights to inform decision-making and drive business strategy. One of the primary responsibilities of data scientists is to collect and preprocess data from various sources, such as databases, APIs, and streaming platforms. They clean and transform the data to ensure its quality and usability for analytics. Using statistical techniques, machine learning algorithms, and data mining methods, Data Scientists analyze the data to identify trends, patterns and correlations. They build predictive models to forecast future outcomes, classify data into different categories, and detect anomalies or outliers.

Data Scientists also develop data-driven solutions to solve complex business problems and optimize processes. They work closely with stakeholders across different departments to understand their data needs and requirements and develop analytical solutions to address specific challenges. In addition to analyzing data, Data Scientists are proficient in programming languages such as Python, R, or SQL to write code and scripts to automate data processing tasks and deploy machine learning models into production environments. Furthermore, Data Scientists are skilled communicators who effectively communicate their findings and insights to non-technical stakeholders through reports, presentations and data visualizations. They collaborate with cross-functional teams to integrate data science solutions into business processes and drive organizational growth and innovation.

Virtual SQL Classes from Noble Desktop

Live online training is one of the most effective ways to learn SQL. This method of training allows users to interact with instructors, ask questions, and have the instructor view their screen. The courses are hands-on with real-world projects, which allows students to apply the knowledge they acquired in the course to projects they are likely to encounter in a variety of professions. The cohort style of live online training also helps students to stay engaged and on track to complete the course.

There are different “flavors” of SQL, including SQL Server, PostgreSQL, and MySQL. All are based on the same underlying programming language and generally follow the same core principles and syntaxes with minor differences.

Before choosing a live online SQL course, you should confirm which relational database system your company needs. If you’re unsure the best place to start is with an understanding of the core principles, which will be similar for all SQL-based programming.

Noble Desktop offers a class called SQL Level 1. In this SQL class, you will dive into the fundamental principles of SQL and relational databases, equipping you with the necessary skills to craft SQL queries adeptly. Through hands-on exercises and expert instruction, you will gain a comprehensive understanding of database architecture, enabling you to navigate tables, columns, and rows within a database with ease. From mastering the art of SELECT statements to employing advanced filtering techniques and using WHERE, AND/OR, IN, and NOT clauses, you will learn how to extract precise data sets efficiently. Moreover, you will explore wildcard filters and mathematical comparisons to fine-tune your queries, ultimately culminating in the mastery of combining data from multiple tables through inner JOINs.

Upon completing this introductory course, you will emerge proficient in writing basic SQL queries specifically tailored for Microsoft SQL Server. Utilizing the free SQL Server Management Studio application, you will harness the power to explore databases and execute your SQL queries seamlessly. Moreover, the skills acquired are transferable across various SQL platforms like Microsoft Access, PostgreSQL, MySQL, etc., with minor syntax discrepancies. By the course’s end, you will possess a robust foundation in SQL, primed to embark on more advanced data analysis and manipulation tasks within diverse database environments.

Noble Desktop also has a class called SQL Level 2. In this intermediate SQL class, you will elevate your SQL expertise by delving into advanced techniques such as Outer Joins, NULL data handling, and group data analysis with aggregate functions. Building upon the foundational knowledge acquired in the SQL Level 1 course, you will deepen your understanding of SQL fundamentals and expand your skill set to effectively join, filter, group, and analyze complex datasets. Through practical, hands-on exercises, you will learn how to utilize Outer Joins to merge datasets, identify and manage NULL values, and harness the power of aggregate functions to perform statistical calculations on grouped data. Additionally, you will master the manipulation of data types using CAST, and gain proficiency in working with dates and time information, essential for accurate data analysis and reporting.

Proficiency in SQL equivalent to completing our SQL Level 1 course is required, encompassing basic querying skills, understanding of filtering techniques (WHERE, LIKE, and wildcards), and familiarity with inner JOINs. Upon completion of this intermediate hands-on course, you will possess a broader repertoire of SQL techniques, empowering you to extract and analyze specific data with precision, thereby facilitating the transformation of raw data into actionable insights for informed decision-making.

The third class in Noble Desktop’s SQL classes is SQL Level 3. In this advanced SQL course, you will transcend your current SQL proficiency to master advanced techniques essential for data analysis, data science, and roles requiring adept manipulation of databases. Through comprehensive instruction, you will delve into subqueries, views, functions, stored procedures, and more, unlocking the full potential of SQL for extracting and manipulating data dynamically. By mastering the utilization of subqueries, you will gain the ability to fetch data from any part of a database and seamlessly integrate it into subsequent queries, enabling advanced data retrieval and analysis. Additionally, you will learn to navigate database permissions by querying views instead of tables, allowing for more flexible and secure data access.

Furthermore, this course equips you with indispensable skills to enhance query logic using CASE statements for If-Else conditions, employ string functions to extract specific segments of text, and execute reusable stored procedures efficiently. By the course's conclusion, you will possess a profound understanding of in-depth SQL techniques, empowering you to excel in various data-driven roles and effectively leverage SQL for complex data manipulation tasks, thereby positioning yourself for success in the dynamic field of data analysis and beyond.

Other Virtual SQL Classes

Other schools like NYIM Training offer a SQL Bootcamp focused on SQL Server. At NYIM Training, you can attend different SQL courses such as the SQL Bootcamp as part of the Data Analytics Bootcamp. This includes courses in Excel, SQL, and Tableau, with the goal of preparing individuals for a position as a Data Analyst. NYC Career Centers also offer a variety of SQL classes. Some other options for virtual SQL classes include:

Practical Programming has a class called SQL Bootcamp. In this data science course, students will embark on a comprehensive journey to master SQL fundamentals essential for efficient data manipulation and analysis. Understanding the pivotal role of SQL in data wrangling, students will learn to harness its power through English-like queries, enabling them to address the challenges of cleaning and manipulation data with ease. With the demand for SQL proficiency skyrocketing across various industries, acquiring this skill will not only enhance students’ decision-making capabilities, but also broaden their career prospects significantly. Throughout the course,s students will be introduced to foundational concepts such as tables, data types, and queries, gradually progressing to advanced querying techniques like filtering, aggregating, and combining information from different tables using join statements and views. The final day of the course will dive into advanced techniques including creating subqueries and utilizing timestamp functions, empowering students to extract meaningful insights and navigate complex data landscapes effectively.

Using Postgres as the primary database platform, this course ensures that the concepts learned are transferable across other databases like MySQL and SQL Server, with minor syntax differences highlighted during class discussions. By the course’s conclusion, students will possess a robust skill set in SQL, equipped to explore and alter data programmatically, understand different data types, and leverage advanced techniques to unlock the full potential of databases for data science endeavors. Whether students are seasoned data professionals or aspiring to break into the field of data science, this course provides a solid foundation for leveraging SQL as a powerful tool in the data manipulation and analysis toolkit.

Computer Training Source, Inc. has a class called SQL Queries Introduction. In this SQL class, students will dive into the foundational principles of SQL, a universal language utilized for managing and manipulating data in relational database management systems (RDBMS). SQL serves as the backbone for various RDBMS platforms such as Oracle, Sybase, Microsoft SQL Server, Access, Ingres, among others, providing a standardized set of commands for tasks like data retrieval, updating, insertion, deletion, creation, and dropping. Throughout the course, students will be guided through essential SQL concepts and commands, including executing simple queries, performing conditional searches, working with functions for data manipulation, organizing data efficiently, retrieving data from multiple tables using joins, and exporting query results for further analysis or presentation.

With a structured curriculum encompassing six comprehensive lessons, students will progress from mastering basic query execution to tackling more complex tasks like retrieving data from multiple tables and exporting query results. By the course’s conclusion, students will possess a solid understanding of SQL fundamentals, equipping them with the skills necessary to interact effectively with databases across various RDBMS platforms and empowering students to leverage SQL for data manipulation and retrieval tasks in their professional endeavors. This course offers a structured approach to mastering SQL and unlocking its potential for efficient data management and analysis.

Borough of Manhattan Community College has a class called Intermediate SQL for Data Analytics. In this SQL class, students will elevate their database management skills by exploring advanced techniques that enable them to effectively manage and query data with greater precision and efficiency. By expanding their understanding of the SQL language, they will gain the ability to create and comprehend queries beyond the basics, empowering them to extract valuable insights from databases with ease. Through a comprehensive series that spans from foundational concepts to advanced techniques, this course equips students with the necessary tools and knowledge to navigate complex data landscapes and optimize their data querying capabilities.

Moreover, by completing this course, students will not only enhance their proficiency in SQL but also prepare themselves for the Microsoft Certified Professional (MCP) Exam 98-364. Earning this certification demonstrates to employers that students’ competence and foundational knowledge in relational databases, particularly Microsoft SQL Server. This credential serves as a testament to their expertise in SQL and database management, opening doors to various career opportunities in data-related roles and showcasing their commitment to professional growth and excellence in the field.

Jigsaw Labs has a class called Python and SQL for Data Analysis. In this data science course, students will embark on a comprehensive learning journey designed by a seasoned Flatiron School lead instructor and curriculum writer, offering a coding bootcamp-quality experience without requiring students to leave their current jobs. Through a structured curriculum, students will dive into Python, SQL and HTML, equipping them with the essential skills to collect data from various online sources, whether it’s scraping web pages or retrieving data from APIs. Classes are conducted via online lectures, supplemented with over 100 readings and hands-on labs that students will complete during class sessions, ensuring a dynamic and immersive learning experience.

This course serves as the first part of the data science career course at Jigsaw Labs, providing a solid foundation in Python, SQL, APIs, and web scraping. Whether students are looking to kickstart a career in data science or enhance their existing skills, this course offers a flexible and accessible pathway to acquiring essential data science skills while balancing their current professional commitments. Students will dive into the world of data science and unlock the power of Python and SQL to collect and analyze data from diverse online sources, setting the stage for their continued growth and success in the field.

Remote SQL Corporate Training

Companies with huge amounts of stored data benefit from employees who know how to organize and query it. For companies looking to train their employees in SQL, virtual training is available. You can send participants to regularly scheduled group classes held virtually or schedule a private session for your team. Custom classes can be conducted in SQL Server, PostgreSQL, or MySQL. Email Noble Desktop at corporate@nobledesktop.com for more information about getting SQL training for your workplace.

Top Certificate Programs

Top Courses

Top Certificate Programs

Top Certificate Programs

Top Courses

Top Certificate Programs

Top Courses

SQL Bootcamp Learn The Skills Guarantee™

Key Insights

Learn More About Live Online SQL Courses

What Will I Learn in an SQL Class?

How Long Will it Take to Learn SQL?

What Skills Should I Learn Alongside SQL?

Is it Better to Learn SQL Virtually or Online?

Virtual SQL Classes from Noble Desktop

Remote SQL Corporate Training

Top Bootcamp Programs That Include SQL

Live Online SQL Courses by School

SQL Bootcamp

SQL Level I

SQL Level II

SQL Level III

SQL Bootcamp

SQL Level I

SQL Level II

SQL Level III

SQL Querying - Basic

SQL Querying - Advanced

MySQL Workbench: Data Modeling & Development

Administering Microsoft SQL Server 2012/14/16 Databases (70-462)

SQL Bootcamp

SQL for Beginners Training Course

SQL Intermediate to Advanced Training Course

SQL Server Reporting Services (SSRS) Training Course

Introduction To SQL Databases

Querying In Microsoft SQL Server

Administering Microsoft SQL Server Databases

Developing Microsoft SQL Server Databases

SQL basic course

SQL Server 2019 administration course

Programming Logic & SQL Databases Course

Database Administrator Path

Database & Data Intelligence Path

Live Online SQL Corporate & Onsite Training Noble Desktop

Related Classes

Live Online SQL
Corporate & Onsite Training