Data Analytics
Course Description
This 16-week, part-time program is designed to transform individuals into proficient Junior Data Analysts. It offers hands-on training in essential data analytics tools including Excel, Power BI, SQL, Python, and ChatGPT AI. The curriculum comprehensively covers data analysis, data quality, data visualization, and statistics for data-driven decision-making. Emphasizing job readiness, the course also includes professional development, resume building, and interview strategies, culminating in a certification that prepares participants to tackle real-world data challenges and launch or advance their careers in the dynamic field of data analytics.
Course Goals
In today's competitive landscape, data analysis expertise is crucial. Our curriculum goes beyond theory, focusing intensively on practical application so you gain the confidence and hands-on experience that employers are actively seeking.
- Hands-On Mastery: Engage in practical exercises and real-world projects from day one, solidifying your understanding.
- Industry-Essential Tools: Gain expertise in the most powerful and widely used data analytics tools:
- Microsoft Excel: Master advanced data manipulation, analysis, and comprehensive reporting.
- Power BI: Create dynamic, compelling dashboards and stunning data visualizations.
- SQL (Structured Query Language): Become proficient in querying, managing, and extracting valuable information from large datasets.
- Python for Data Analysis: Utilize Python's robust libraries for advanced data processing, statistical analysis, and modeling.
- ChatGPT AI: Learn to leverage cutting-edge Artificial Intelligence for enhanced data interpretation, problem-solving, and efficient analytical workflows.
- Deep Statistical Understanding: Develop a strong foundational understanding of statistics for data-driven decision-making, ensuring you can interpret complex data accurately and contribute valuable insights.
- Accelerated Job Readiness: Benefit from dedicated, practical modules on resume development and proven interview strategies, preparing you to confidently navigate the job market and secure your first role as a Junior Data Analyst.
- Expert Instructor: Learn from a seasoned professional with extensive experience in Project Management, manufacturing, and high proficiency in Data Analytics and Data Science.
What You'll Achieve: Your Data Analytics Learning Outcomes
By the end of this transformative Data Analytics course, you will possess the capabilities to:
- Execute Data Analysis: Confidently apply prominent tools like Excel, Power BI, SQL, Python, and ChatGPT AI for in-depth data analysis.
- Ensure Data Quality: Implement strategies to maintain accuracy and reliability in your datasets.
- Craft Engaging Visualizations: Design and create compelling reports and dashboards that effectively communicate data stories to stakeholders.
- Address Real-World Challenges: Utilize your newfound understanding, including leveraging ChatGPT AI, to solve complex data-related problems.
- Enhance Career Prospects: Be prepared to either embark on a new data analytics career or significantly enhance your current role with valuable data skills
Week
1
( 18 Hours )
Intro to Analytics and Excel
- Focus on Excel as a crucial tool for data analysis
- Learn the importance and practical uses of Excel
- Explore workbook creation
- Understand common Excel functions
- Study conditional aggregation
- Discover pivot tables and charts
- Examine slicers and time slicers
- Build a strong foundation for the remainder of the course
Week
2
( 18 Hours )
Learn Microsoft Excel
- Learn to apply conditional formatting in Excel
- Discover how to import data effectively
- Understand the process of adding to data models
- Master pivoting using multiple tables
- Gain expertise in Excel's PowerQuery and PowerPivot
- Dive into Data Analysis Expressions (DAX)
- Explore creating measures and KPIs
- Perform what-if analysis in Excel
- Get acquainted with the data analysis tool package
- Participate in cohort quizzes, assignments, and exercises to reinforce learning
Week
3
( 18 Hours )
SQL for Data Analysis (Part 1)
- Understand the anatomy of an SQL query
- Learn about Common Table Expressions in SQL
- Explore generating data and creating a Date Dimension
- Dive into random data generation and sampling techniques
- Grasp train/test split implementation with SQL
- Test your knowledge with a Basic SQL for Data Analysis quiz
- Delve into describing a series in descriptive statistics
- Discover how to describe a categorical series
- Assess your understanding with a Descriptive Statistics quiz
Week
4
( 18 Hours )
SQL for Data Analysis (Part 2)
- Master the concept of grouping in SQL
- Learn about conditional aggregates and subtotals
- Evaluate your understanding with a Grouping and Subtotals quiz
- Discover aggregate expressions in SQL
- Understand window frames and their application
- Explore accessing next and previous rows in SQL
- Dive into SQL ranking functions
- Test your knowledge with a Running and Cumulative Aggregation quiz
Week
5
( 18 Hours )
SQL for Data Analysis (Part 3)
- Learn to compare missing values in Interpolation
- Explore back filling and forward filling techniques
- Understand linear interpolation
- Test your knowledge with an Interpolation quiz
- Discover the concept of binning in data analysis
- Learn about equal-height binning
- Dive into equal-width binning
- Assess your understanding with a Binning quiz
Week
6
( 18 Hours )
Learn Power BI (Part 1)
- Discover what PowerBI is and its purpose
- Learn data visualization best practices
- Understand the high-level overview and components of PowerBI
- Gain experience in importing data and creating visuals
Week
7
( 18 Hours )
Learn Power BI (Part 2)
- Master data transformation techniques in PowerBI
- Learn how to create relationships between data sets
- Engage with cohort quizzes, assignments, and exercises to reinforce learning
Week
8
( 18 Hours )
Learn Power BI (Part 3)
- Learn how to publish reports in PowerBI
- Discover how to create engaging dashboards
- Dive into real-time visuals for dynamic data representation
- Explore custom visuals for tailored visualizations
- Understand security and sharing practices in PowerBI
- Maximize usage and efficiency of PowerBI tools
- Enhance learning through cohort quizzes, assignments, and exercises
Week
9
( 18 Hours )
Python for Analysis (Part 1)
- Get started with Python for analytics
- Understand essential data structures in Python
- Learn about control flow and built-in functions
- Explore Numpy, an external library for numerical computing
- Discover Scipy, an external library for scientific computing
- Practice using Numpy and Scipy through exercises
- Review solutions for Numpy and Scipy exercises
- Work with comma-separated files (CSV)
- Learn how to handle JSON files
- Manage raw files in Python
- Exercise: Read and analyze the Auto MPG dataset
- Review solutions for reading the Auto MPG dataset
Week
10
( 18 Hours )
Python for Analysis (Part 2)
Describing Data:
- Learn about statistics and counts in data analysis
- Understand reshaping the data
- Practice group-by aggregations through exercises
- Review solutions for group-by aggregations exercises
Cleaning Data:
- Explore how to handle missing data
- Learn to identify and manage outliers
- Understand the importance of scaling data
- Dive into working with categorical data
- Exercise: Clean the Auto MPG dataset
- Review solutions for cleaning the Auto MPG dataset
Week
11
( 18 Hours )
Python for Analysis (Part 3)
Visualizing Data:
- Get introduced to data visualization techniques
- Learn to create scatter plots for data representation
- Understand and create bar plots for data visualization
- Explore visualizing data distributions
- Learn to represent data using line graphs
- Discover the use of heat maps in data visualization
- Master the art of multi-plot grids for data representation
- Exercise: Visualize the Auto MPG dataset
- Review solutions for visualizing the Auto MPG dataset
- Test your understanding with self-assessment questions
Week
12
( 18 Hours )
Final Project Review & Career Prep
Final Project Options:
- Create a Sales Analysis Dashboard using Excel or Power BI
- Perform Social Media Analytics with Power BI
Career Preparation:
- Get assistance with resume review and creation
- Participate in a mockup interview to prepare for real interviews
- Learn to create an effective LinkedIn profile for job search
Main Campus: 2800 S. 192nd St. Ste 206, Seatac, WA 98118
Admin Office: 2265 116th Ave NE, Bellevue, WA 98004
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Admin Office: 2265 116th Ave NE, Bellevue, WA 98004
Join our newsletter to stay up to date on features and releases.