ITTA is certified by EDUqua and is an authorized training provider for Adobe, Cisco, Microsoft, Prince2, and Scrum. The school partners with Swiss organizations to help unemployed and underemployed students access professional development training.
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In this class, Students learn to write SQL queries and draw benefit from a database. The chief focus is on elaborating SELECT queries, but students also learn to organize data results, retrieve data from multiple tables, and export query results.
In this class, students are taught to use advanced SQL operators and expressions. Triggers, columns, user-defined functions, SQL grouping functions, and error handling are all covered as well.
This training teaches students how to create spreadsheets, execute simple calculations, and make a simple graph. Filters, sorting data, and using predefined chart styles are also covered.
Students in this Excel class learn to copy data, group spreadsheets, and apply visual elements for added interest. Headers, footers, margins, and page breaks are also covered in this brief course’s curriculum.
Performing calculations in a spreadsheet and learning to create formulae are the chief objectives of this short-term Excel class. The function library is covered as well, so that students will be able to bring logical operators, statistics, and even trigonometry to their spreadsheets.
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Microsoft Excel is the leading spreadsheet application and data analytics tool. With Excel, you can create charts, tables, automate workflow, track budgets and financials, and much more.
SQL is short for Structured Query Language and refers to a programming language designed for relational databases. SQL organizes data and allows for queries and sorting of data.
Python is an easy-to-read, versatile object-oriented programming language. It is often compared to Java, Ruby, and Perl. It is available under an open-source license and is a favorite among programmers.
Data science is one of the fastest-growing career fields, with competitive salaries and nearly endless opportunities for specialization. Data science uses machine learning algorithms, statistics and other analytic tools to understand data.
Data analytics is the process of analyzing raw data in order to draw conclusions. Data analytics are used to study all kinds of data, including productivity, production, profit/loss and much more.
Machine learning is a subset of artificial intelligence and involves creating programs that learn from data and optimize. Machine learning is prevalent in our everyday lives, from the recommendation engines for music and TV to the search engines and the voice assistants. Machine learning models leverage vast amounts of past data to learn to solve problems on their own and predict future outcomes. With the power and prevalence of machine learning, it is a highly in-demand set of skills, and the field of machine learning continues to grow.
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