Udemy

Become a Data Analyst + AI Python, SQL, Excel , Power BI ,DW

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  • 13,089 Students
  • Updated 3/2026
4.2
(2,144 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
14 Hour(s) 22 Minute(s)
Language
English
Taught by
247 Learning
Rating
4.2
(2,144 Ratings)
3 views

Course Overview

Become a Data Analyst + AI Python, SQL, Excel , Power BI ,DW

Master Python, SQL, Power BI and AI tools. The complete 2026 analyst skill set enterprises are hiring for.

Data analysis is a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.

Data analysts are in high demand across all sectors, such as finance, consulting, manufacturing, pharmaceuticals, government and education.

The ability to pay attention to detail, communicate well and be highly organised are essential skills for data analysts. They not only need to understand the data, but be able to provide insight and analysis through clear visual, written and verbal communication.


Some responsibilities of a data analyst includes:


  • Developing records management processes and policies

  • identify areas to increase efficiency and automation of processes

  • set up and maintain automated data processes

  • identify, evaluate and implement external services and tools to support data validation and cleansing

  • produce and track key performance indicators

  • develop and support reporting processes

  • monitor and audit data quality

  • liaise with internal and external clients to fully understand data content

  • gather, understand and document detailed business requirements using appropriate tools and techniques

  • design and carry out surveys and analyse survey data

  • manipulate, analyse and interpret complex data sets relating to the employer's business

  • prepare reports for internal and external audiences using business analytics reporting tools

  • create data dashboards, graphs and visualisations

  • provide sector and competitor benchmarking

  • mine and analyse large datasets, draw valid inferences and present them successfully to management using a reporting tool


In this course we will perform some task of a Data Analyst using Python ,Excel, SQL, and Power BI. We will connect to a variety of data sources, perform data transformation ,cleaning and exploration . We will create dashboards to visual data .


Course Content

  • 17 section(s)
  • 162 lecture(s)
  • Section 1 Introduction
  • Section 2 Python and Jupyter Notebook Setup
  • Section 3 Data Analysis & Visualization with Python & Jupyter Notebook
  • Section 4 Data Analysis & Visualization with Excel
  • Section 5 Microsoft SQL Server Setup
  • Section 6 Data Exploration & Analysis with SQL
  • Section 7 Power BI Setup
  • Section 8 Power BI Overview
  • Section 9 Data Analysis & Visualization with Power BI
  • Section 10 Analyse & consume database data with Power BI
  • Section 11 Transforming Data with Power BI
  • Section 12 Visual Studio Setup
  • Section 13 AI Powered Data Warehouse
  • Section 14 Python Setup
  • Section 15 Analytics & Business Intelligence for AI Modelled Data Warehouse
  • Section 16 Enterprise Data Analysis Using Oracle SQL and Oracle Autonomous AI Database
  • Section 17 Capstone Project

What You’ll Learn

  • Perform data analysis & visualization with Python, Perform data analysis & visualization with Excel, Perform data exploration and analysis with SQL, Perform data analysis & visualization with Power BI, Write SQL Queries to explore and analyse data, Connect to multiple data sources with Power BI, Clean & transform data, Create Dashboards with Power BI, Write SQL temporary table queries to extract and query data, Write SQL CTE queries to extract and query data


Reviews

  • E
    Eda Nur Şahin
    2.0

    It could be much better

  • A
    Anthony
    4.0

    there is some small steps should the instructor talk about like use the upper letter when the variable name in upper and some small steps in the working

  • O
    Olujuyitanolusegun
    3.0

    Still learning

  • A
    Amruta Tatakoti
    5.0

    good, easy to understand

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