Data Analysis Course

This course is balanced for novice data analysts, but the material is full of advanced data analytics information, challenges, and examples. Here you will not only gain a general understanding of what data analysis is, but you will also see real data analysis solutions that use the tools from this course. Get to know and see live the requirements of employers and the real challenges for data analysts in job selection.

For those looking for an answer if data science is for You - this is the place!



NEW. Fully funded data analytics course for employed and unemployed.

UZT vizualas

The basic course consists of the following modules:

DASQL

Data queries using the SQL language.
Duration: 21 h.

SQL is the beginning of the data analysis journey. With this language, we will extract data from servers and automate data exchange.

During the course we will examine in detail the following and related topics:

  • SQL Servers;
  • Database Structures;
  • Table Relationship;
  • Table Keys;
  • SQL Queries;
  • Data Filtering;
  • Data Aggregations;
  • Data Grouping;
  • Subqueries;
  • Table Joining;
  • SQL Functions;
  • Data Types;
  • Data Base & Table Creation & Deletion.

DAPBI

Data editing and visualization using Microsoft Power BI.
Duration: 18 h.

Power BI is an indispensable tool for interactive data visualization. In this tool, we will implement both the acquired SQL knowledge and Python programming, combining everything into a single and complex analysis.

During the course we will examine in detail the following and related topics:

  • Power BI Desktop;
  • Power BI Service;
  • Power BI Gateway;
  • Different Data Sources;
  • Various connections;
  • Connection to Server Data;
  • Query Editor;
  • KPI Dashboards;
  • AI Analytics;
  • Forecasting;
  • Tooltips;
  • Table Relationship;
  • What-if parameter;
  • Bookmarks;
  • Drill Actions;
  • DAX;
  • Power Query;
  • SQL Query;
  • Python integration;
  • Data from WEB;
  • Custom Theme;
  • Templates.

DAPTN

Advanced data analysis using the Python programming language.
Duration: 36 h.

Python is the best that modern programming has to offer data scientists. With the help of this tool, we will not only learn to do what you already know with the help of Excel and similar tools, but we will also touch the wonderful world of artificial intelligence.

During the course we will examine in detail the following and related topics:

Python basics

  • Basics of Programming Languages;
  • Code Editors;
  • Python Syntax;
  • Basic Python Functions;
  • Python Data Types;
  • Variables;
  • Operators;
  • Basic Mathematics in Python;
  • Data Sets;
  • Methods;
  • Indexing;
  • Slicing;
  • Casting;
  • Unpacking;
  • Loops;
  • List Conprehension;
  • Functions;
  • Lambda Functions;
  • Classes;
  • Built-in Python Modules;

Python application for data analytics

  • Third party Python Modules;
  • Arrays;
  • Introduction to vector mathematics with the NumPy module;
  • Advanced data analysis with Pandas module;
  • Data exchange with SQL servers by combining SQL code with Python code;
  • Data visualization with Pandas module;
  • Data visualization with Matplotlib module;
  • Data visualization with Seaborn module;
  • Basics of machine learning using the SKLearn module;