AI Data Analysis

Build job ready and must have AI skills for an in demand career


Contact Us

About this Course:


Prepare for a career in the high-growth field of data analytics. In this program, you will learn in-demand skills like Python, Excel, and SQL to get job-ready.


Data analysis is the process of collecting, storing, modeling, and analyzing data that can inform executive decision-making, and the demand for skilled data analysts has never been greater. 


This program will teach you the data skills employers are seeking for data analytics roles. It will not only help you start your career in data analytics, but also provides a strong foundation for future career development in other paths such as data science, artificial intelligence, deep learning, or data engineering. 


You’ll learn the latest skills and tools used by professional data analysts including Excel spreadsheets, Python, Pandas, Numpy, Jupyter Notebooks, and more. You’ll work with a variety of data sources and project scenarios to gain practical experience with data manipulation and applying analytical skills. You'll also have the option to learn how generative AI tools and techniques are used in data analysis.


You will build a portfolio of projects to showcase your expertise in your job search.


Throughout the program, you’ll complete hands-on projects and labs and gain a firm grasp on the required technical skills to effectively gather, wrangle, mine, and visualize data, as well as the soft skills for working with stakeholders and storytelling with data to engage your audience.


Projects:

  • Import, clean, and analyze fleet vehicle inventory with Excel pivot tables
  • Use car sales key performance indicator (KPI) data to create an interactive dashboard with visualizations
  • Extract and graph financial data with the Pandas data analysis Python library
  • Use SQL to query census, crime, and school demographic data sets
  • Wrangle data, graph plots, and create regression models to predict housing prices with data science Python libraries
  • Create a dynamic Python dashboard to monitor, report, and improve US domestic flight reliability

What you will learn

  • Master the most up-to-date practical skills and tools that data analysts use in their daily roles
  • Learn how to visualize data and present findings using various charts in Excel spreadsheets and Tableau
  • Develop working knowledge of Python language for analyzing data using Python libraries like Pandas and Numpy, and invoke APIs and Web Services 
  • Gain technical experience through hands on labs and projects and build a portfolio to showcase your work

Skills you will gain

Plotly, Data Cleansing, Data Wrangling, Big Data, Data Transformation, Jupyter, Python Programming, Professional Networking, Exploratory Data Analysis, Dashboard, Interactive Data Visualization

Modules

  1. Introduction to Data Analytics
  2. Excel Basics for Data Analysis
  3. Data Visualization and Dashboards with Excel and Cognos
  4. Python for Data Science, AI & Development
  5. Python Project for Data Science
  6. Databases and SQL for Data Science with Python
  7. Data Analysis with Python
  8. Data Visualization with Python
  9. IBM Data Analyst Capstone Project
  10. Generative AI: Enhance your Data Analytics Career
  11. Data Analyst Career Guide and Interview Preparation

Learning Objectives

Basics of Python Coding




  • Stop here Write and run python code inside a special programming environment called a Jupyter notebook
  • Write simple python programs that display text or numbers on the screen, including the result of calculations that python has carried out for you
  • Interact with an AI large language model via the python programming language
  • Ask a chatbot for help with common coding questions, like how to carry out a task, help fix a bug in the code, or explain what an error message means
  • Store data in a variable for use in subsequent lines of code
  • Write customizable prompts for an LLM using a special data type in Python called a formatted string


Automating Tasks with Python


  • Use lists to store multiple items of data, for example a list of strings that form a to do list
  • Use a for loop to access all items in a list sequentially and use python to perform an action on each item automatically
  • Store data items and their associated lookup key in a python dictionary
  • Compare data items in python using special relational operators like less than, greater than, equal to
  • Describe the Boolean data type and know that the result of comparing two data items is a Boolean, either true or false
  • Use if statements to ask a python program to make a decision in response to data it sees


Working with Your Own Data and Documents in Python

  • Use python to read data inside a document and store it as strings or numbers
  • Pass text from documents to an LLM and ask it to analyze it in a specific way, for instance by finding and highlighting restaurant names within food blog articles
  • Automate data analysis tasks for multiple documents using for loops
  • Write and save data from your python programs to a file on your computer
  • Turn blocks of code into reusable functions that can be used in python programs
  • Use an AI to suggest the best tourist activities for all the destinations on a vacation itinerary


Extending Python with Packages and APIs



  • Load and use built-in modules in python to enable new functionality, like performing math and statistic calculations
  • Import functions from external files and 3rd party libraries to use pre-existing code that solves common problems
  • Work with a chatbot to identify useful 3rd party packages for your task, and then write code for using those packages
  • Install 3rd party packages available online to make them available in your Jupyter notebook
  • Use application programming interfaces (APIs) to access data and tolls from the internet and use them in your programs
  • Install python and Jupyter on your own computer using the Anaconda package