Data Science with Python Certification Training Courses in Aurora, IL United States

Data Science with Python Training Program Overview Aurora, IL

Data Science with Python Certification: The Non-Negotiable Lever for High-Value Data Science Roles

You've spent years in Excel or basic SQL, generating historical reports that tell management what they already knew last quarter. Your job is analysis, but your output is descriptive, not predictive. The industry has moved on: companies in Aurora, IL are building predictive maintenance models, fraud detection systems, and customer churn scores. They're not looking for report writers; they're paying a 50%+ premium for certified Data Scientists who can code in Python and translate complex statistical outcomes into clear, scalable, and profitable business solutions through Data Science with Python Training. You're currently stuck because your resume lacks the keywords: Pandas, Scikit-learn, Hypothesis Testing, REST APIs, and Deployment Pipelines. HR filters are scanning for certified proof that you can handle the math and the code required to deliver actual business value through a recognized Data Science with Python certification. That stops now. This isn't another generalized Python course. This Data Science with Python course is designed by professional Data Scientists to bridge the massive gap between data analysis and rigorous predictive modeling and productionization. You will learn the why behind the how: understanding the assumptions of a model, dealing with messy real-world data issues (missing values, outliers), and critically, interpreting model coefficients to drive business strategy—not just getting a high R-squared. We built this for ambitious Analysts, BI Developers, and Statisticians in Aurora, IL who need to rapidly upskill. You get direct, hands-on labs using Jupyter Notebooks, extensive case studies in finance and e-commerce, and personalized feedback on your model code. Beyond the exam, you leave with a portfolio of robust models—from market basket analysis to classification algorithms—ready to impress any senior Data Science Manager. Stop settling for low-impact reporting. Start building the models that dictate multi-crore business decisions.

Data Science with Python Training Course Highlights

More Than a Course—It's Your Career Accelerator

Rigorous Statistical Modeling

Master the three pillars of enterprise analytics—Regression, Classification, and Clustering—through a comprehensive Data Science with Python program using Scikit-learn.

Live Python Coding Labs

Engage in 30+ hours of intensive, hands-on practice in Jupyter and Spyder for data manipulation, visualization, and complex model construction.

Exhaustive Practice Scenarios

Access over 2,000 questions focused on statistical assumptions, model interpretation, and practical Python coding output to cut through generic test banks.

Critical Library Mastery

Gain practical fluency in the packages that matter most in production environments: Pandas, Scikit-learn, NumPy, and Statsmodels.

Portfolio-Ready Final Project

Complete an end-to-end Data Science project, from data cleaning to basic deployment, designed to be showcased to employers in a highly competitive analytics market.

24x7 Expert Guidance

Receive immediate, high-quality support from certified Data Scientists throughout your training, covering Python code errors, statistical confusion, and model validation issues.

Practical Application

In this Data Science with Python Certification Training Program, participants will work on real-world projects to develop and deploy machine learning models using Python. They will apply statistical modeling techniques to analyze and visualize data, identifying key trends and patterns. The program focuses on practical application of concepts, rather than theoretical foundations.

The training will cover a range of topics, including regression, decision trees, clustering, and neural networks. Participants will learn how to use popular Python libraries such as NumPy, Pandas, and Scikit-learn to implement and evaluate machine learning algorithms. They will also work with real-world datasets to develop and refine their models.

In Aurora, IL, this practical application of data science skills is highly valuable, particularly in industries such as healthcare and finance. Participants in this program will be equipped to bring data-driven insights to their work, making informed decisions and driving business success.

Corporate Training

Tailored programs for teams with enterprise support

Learning Models

Choose from digital or instructor-led training for a customized learning experience.

LMS Platform

Access an enterprise-grade Learning Management System built for scalability and security.

Pricing Options

Pick from flexible pricing plans that fit your team size and learning goals.

Performance Dashboards

Track progress with intuitive dashboards for individuals and teams.

24x7 Support

Get round-the-clock learner assistance whenever you need help.

Account Manager

Work with a dedicated account manager who ensures smooth delivery and support.

Ready to transform your team?

Get a custom quote for your organization's training needs.

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Work Responsibilities

Data scientists with Python skills are responsible for collecting, processing, and analyzing large datasets to gain meaningful insights. They design and implement machine learning models to solve complex business problems, using techniques such as regression, decision trees, and clustering. This involves working with stakeholders to understand business needs and developing data visualizations to communicate results.

The work responsibilities of a data scientist with Python skills also include developing and deploying predictive models, identifying areas for improvement, and refactoring code as needed. Participants in this Data Science with Python Certification Training Program will learn how to write efficient and scalable code, using best practices to ensure data quality and model performance. They will also learn how to collaborate effectively with cross-functional teams.

In Aurora, IL, data scientists with Python skills are in high demand, particularly in companies that rely on data-driven decision making. Participants in this program will be well-prepared to take on a variety of work responsibilities, from data analysis and visualizations to machine learning and model deployment.

Upcoming Schedule

Join the next batch that fits your timezone

Skills You Will Gain In Our Data Science with Python Training Program Aurora, IL

From Knowledge to Actionable Intelligence

Statistical Inference & Hypothesis Testing

Move beyond p-values. You will learn to design rigorous A/B tests and draw statistically valid conclusions that confidently inform million-dollar business decisions.

Data Manipulation & Wrangling

Become ruthlessly efficient with a hands-on Data Science with Python course. Master the Pandas/NumPy stack to clean, transform, and reshape messy, real-world data from Aurora, IL systems (e.g., SQL, JSON, CSV) in seconds.

Predictive Modeling (Regression)

Build robust forecasting systems as part of an advanced Data Science with Python certification. You will master Linear and Generalized Linear Models, understanding assumptions, diagnostics, and interpretation of coefficients for critical business drivers using Scikit-learn.

Advanced Classification Techniques

Solve real-world classification problems (e.g., fraud, churn) within a structured data science with python program. You will implement Logistic Regression, Decision Trees, and Random Forests in Python, and interpret their output.

Unsupervised Learning (Clustering/Association)

Uncover hidden customer segments. You will master K-Means clustering and Association Rules (Market Basket Analysis) to drive personalized marketing and inventory strategy using datascience with python.

Advanced Data Visualization

Stop sending ugly charts. Master Matplotlib and Seaborn to create compelling, publication-quality data visualizations that effectively communicate complex model results to non-technical stakeholders.

Who This Program Is For

Ideal Candidates for Data Science with Python Certification

Individuals currently working as BI Analysts

Those in roles as Market Researchers

Professionals categorized as Software Engineers

Leaders holding the title of IT Professionals

Managers focused on Data Analysts

Professionals working as Statisticians & Economists

If you have a solid analytical mindset, basic programming exposure, and are tired of being overlooked for high-impact Python-based roles, this intensive training in Python and statistical modeling is your required path to a Data Scientist title.Opening doors to entry level data science jobs as well as advanced roles.

Career Relevance

Data science with Python certification is highly relevant to a range of career paths, including data scientist, data analyst, and business analyst. With this certification, participants will have a strong foundation in machine learning, statistical modeling, and data visualization, making them highly competitive in the job market. They will be able to work with large datasets, develop and deploy predictive models, and communicate results to stakeholders.

The certification also demonstrates a high level of proficiency in Python, which is a highly sought-after skill in many industries. Participants in this program will learn how to work with popular Python libraries such as NumPy, Pandas, and Scikit-learn, and will be able to apply these skills to real-world projects. They will also learn how to collaborate effectively with cross-functional teams.

In Aurora, IL, companies such as Caterpillar, Navistar, and the City of Aurora rely heavily on data-driven decision making. With this certification, participants will be highly competitive in the job market, and will have a strong foundation for a successful career in data science.

Data Science with Python Certification Training Program Roadmap

The Step-by-Step System for First-Attempt Success

Step 1: Secure Your Path

Commit to the course and establish a rigorous 6-week Python study plan designed to solidify your learning trajectory.

Step 2: Master the Code

Achieve fluency in Python programming, Pandas, and the NumPy ecosystem through intensive labs in this hands-on datascience with python curriculum.

Step 3: Internalize the Math

Conquer Hypothesis Testing and Regression analysis by focusing on the interpretation of results rather than just the mathematical formulas.

Step 4: Build the Portfolio

Construct, validate, and document complex Classification and Clustering models using Scikit-learn and real-world data within a practical data science with python program.

Step 5: Find & Fix Flaws

Pinpoint and eliminate technical weaknesses using 2,000+ scenario questions that rigorously test your statistical and Python coding accuracy.

Step 6: Execute & Pass

Take your certification exam with unshakeable confidence in your predictive modeling and Python execution skills.

Step 7: Leverage Your Credential

Apply for senior Data Scientist and ML Engineer roles where certified proficiency in Python and data science is a mandatory requirement.

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Why get Data Science certified?

The Credential That Ends the Gatekeeping

Command High-Level Attention

Stop getting filtered out by HR bots. Secure the senior Data Scientist and modeling interviews your statistical and technical experience already deserves.

Access Premium Compensation

Unlock the higher salary bands and specialized roles reserved for professionals who can build and deploy scalable, complex statistical models using Python.

Pivot to Strategic Leadership

Transition from descriptive reporting to strategic, predictive analytics, earning a mandatory seat at the core business decision-making table.

Eligibility and Pre-requisites for Data Science with Python Certification

Data Science with Python Certification Requirements

Objective: To certify your practical expertise in statistical modeling within the Python ecosystem. Candidates must demonstrate proficiency across the following pillars:

Eligibility Criteria:

Formal Statistical Training: Completion of a comprehensive program covering inferential statistics, regression analysis, and machine learning algorithms.

Python Coding Proficiency: The mandatory, demonstrable ability to write, debug, and optimize Python code for data cleaning, visualization, and model building using Pandas and Scikit-learn.

Domain Knowledge: A strong analytical mindset and foundational understanding of the business problems that predictive modeling is designed to solve.

Growth

The Data Science with Python Certification Training Program is designed to help participants grow their skills and knowledge in machine learning, statistical modeling, and data visualization. Through a combination of lectures, hands-on exercises, and real-world projects, participants will develop a deep understanding of data science concepts and techniques. They will also learn how to apply these concepts to real-world problems, using popular Python libraries such as NumPy, Pandas, and Scikit-learn.

The program emphasizes growth and development, with a focus on practical application and real-world experience. Participants will have the opportunity to work on a variety of projects, from data analysis and visualization to machine learning and model deployment. They will also learn how to collaborate effectively with cross-functional teams.

In Aurora, IL, companies such as Caterpillar, Navistar, and the City of Aurora are investing heavily in data science and analytics. With this growth in demand, participants in this program will have a wide range of career opportunities available to them.

Course Modules & Curriculum

Comprehensive modules covering all knowledge areas

Module 1 Module 1: Foundational Python Programming and Data Structures ▾

Lesson 1: Introduction to Business Analytics and Python

Understand the role of the Data Scientist, the Analytics Life Cycle, and the advantages of Python over traditional tools. Install Jupyter/Spyder and set up the working environment as part of this Data Science with Python course.

Lesson 2: Python Programming and Data Structures

Master core Python data types (lists, tuples, dictionaries) and control structures (loops, conditionals). Learn to import and export data from common formats (CSV, JSON).

Lesson 3: Pandas Mastery and Efficient Data Manipulation

Master the Pandas library and the NumPy array structure. Achieve fluency in data cleaning, transformation, and reshaping messy, real-world data efficiently.

Module 2 Module 2: Statistical Inference and Hypothesis Testing ▾

Lesson 1: Introduction to Statistics for Data Science

A brutal, practical overview of descriptive statistics, probability distributions, and inferential concepts (sampling, Central Limit Theorem). Focus on application, not academic proofs.

Lesson 2: Hypothesis Testing I (T-Tests and ANOVA)

Master the core process of hypothesis formulation, test selection, and p-value interpretation. Hands-on implementation of T-tests and ANOVA in Python for comparing means and making valid conclusions.

Lesson 3: Hypothesis Testing II (Chi-Squared and Non-Parametric)

Apply Chi-Squared tests for categorical data analysis. Understand when to use non-parametric tests and implement them using Python's Statsmodels, ensuring you never draw a statistically invalid conclusion from real-world data.

Module 3 Module 3: Predictive Modeling (Regression and Classification) ▾

Lesson 1: Regression Analysis

Master the assumptions and interpretation of Simple and Multiple Linear Regression. Learn model diagnostics, variable selection, and how to effectively communicate model coefficients to business leadership using Scikit-learn.

Lesson 2: Classification Models (Logistic Regression)

Dive deep into Logistic Regression for binary classification problems. Understand concepts like log-odds, ROC curves, AUC, and how to set appropriate threshold values for optimal business impact using Scikit-learn.

Lesson 3: Tree-Based Models (Decision Trees & Random Forests)

Implement powerful non-linear classification models. Master Decision Trees and Random Forests in Python, learning hyperparameter tuning and variable importance interpretation for robust, high-accuracy predictions.

Module 4 Module 4: Unsupervised Learning and Visualization ▾

Lesson 1: Clustering Techniques

Master K-Means and Hierarchical Clustering for identifying hidden customer segments or data anomalies. Learn to interpret cluster validity and size for actionable business strategy using Scikit-learn.

Lesson 2: Association Rule Mining and Model Persistence

Implement the Apriori algorithm for Market Basket Analysis. Learn best practices for model object saving/loading using joblib or pickle for production deployment.

Lesson 3: Advanced Data Visualization

Master Matplotlib and Seaborn to create complex, informative, and visually compelling plots (scatter plots, box plots, heat maps) to clearly communicate model findings and data insights.

Module 5 Module 5: Model Validation, API Deployment, and Advanced Python ▾

Lesson 1: Model Evaluation and Validation

Master key performance metrics (Accuracy, Precision, Recall, F1-Score) and techniques like cross-validation to ensure your models are robust and perform reliably on unseen data.

Lesson 2: Database Connectivity and Advanced Data Sourcing

A practical overview of connecting Python to relational databases (PostgreSQL/MySQL) using libraries like SQLAlchemy—a mandatory enterprise skill.

Lesson 3: Advanced Reporting and Productionization

Learn to create dynamic, reproducible reports and dashboards using Jupyter Notebooks. Final project consolidation, code optimization, and best practices for creating REST APIs for model serving.

Data Science with Python Certification & Exam FAQ

Find answers to common questions about our course and certification

Is Python still relevant for Data Science, or should I just learn R? ▾

Python is the dominant language for production, MLOps, and generalized Data Science due to its expansive libraries (Pandas, Scikit-learn) and ease of integration with enterprise IT systems and web frameworks. Competence in Python is a non-negotiable requirement for high-end deployment and engineering-focused roles.

How much does the Python certification exam cost? ▾

The primary certifications validating Python proficiency (e.g., PCEP, PCAP, or vendor/third-party exams focusing on Scikit-learn and data analysis) vary widely, generally costing between $150 and $400. You must confirm the fee for your chosen vendor.

What are the prerequisites for this Data Science with Python training? ▾

You need foundational knowledge of statistics (mean, median, standard deviation) and some exposure to programming logic. If you struggle with basic analytical thinking, this course is not for you.

How long is the Python certification exam and what is the format? ▾

Exams typically run for 90 to 120 minutes and are often a mix of scenario-based multiple-choice questions testing statistical interpretation and practical sections requiring you to write or debug Python code snippets related to Pandas/Scikit-learn.

What is the passing score for the Python certification exam? ▾

Most certification bodies require a score of around 70-75% to pass. Our simulators are engineered to get you consistently scoring above 85%, making the passing score irrelevant.

Do I need to memorize all the Scikit-learn syntax for the exam? ▾

No. You need to understand the logic, key function calls (e.g., .fit(), .predict()), and correct usage of core packages like Pandas and Scikit-learn. The exam tests your modeling competency and correct methodology, not your memory.

Can I take the Data Science with Python certification exam online from home? ▾

Yes. Most exams for Data Science with Python certification are offered via online proctoring. Be warned: a stable internet connection in Aurora, IL is crucial, as any disconnection often invalidates the attempt.

How do I get hands-on practice with real-world data using Python? ▾

Our course uses sanitized but realistic datasets from Aurora, IL industries (e.g., telecom churn, e-commerce transactions) in every lab, ensuring your models are trained on data complexity that reflects the job market.

How long is my Python certification valid for? ▾

Most data science-related certifications have a validity of 2 to 3 years. Renewal typically requires recertification or completing Continuous Professional Education (CPE) requirements to prove your skills are current.

What Python packages are considered mandatory for a Data Scientist role in Aurora, IL? ▾

Pandas, NumPy, Scikit-learn, and Matplotlib/Seaborn are non-negotiable essentials we focus on. You must be production-fluent in this core stack.

Does this course cover SQL connectivity using Python? ▾

Yes. This Data Science with Python Training cover practical Python libraries like SQLAlchemy for connecting to and interacting with relational databases—a mandatory skill for any Data Scientist working with enterprise data in Aurora, IL.

Will the course cover model deployment or just local development? ▾

We cover the transition to production, focusing on generating clean, reproducible reports using Jupyter Notebooks and discussing best practices for model object saving (pickle/joblib) and deployment methodologies.

What is the role of the NumPy library in Python? ▾

NumPy is crucial for high-performance numerical operations. You must understand how to use its array structure to accelerate data processing and support the linear algebra operations required by Scikit-learn models.

What level of math is required to succeed in the Hypothesis Testing modules? ▾

You need college-level algebra and a firm grasp of foundational statistics (mean, variance). The focus is on interpreting statistical output and model diagnostics, not complex matrix algebra.

Is this certification relevant for Big Data environments like Hadoop/Spark? ▾

Yes. Python has native integration capabilities with Big Data platforms (PySpark, Dask). Mastering the core statistical modeling in Python is the mandatory first step before integrating with scale-out architectures.

Skill Gap

The Data Science with Python Certification Training Program is designed to address a significant skill gap in the industry, particularly in machine learning and statistical modeling. With this certification, participants will gain a strong foundation in data science concepts and techniques, including regression, decision trees, clustering, and neural networks. They will also learn how to work with popular Python libraries such as NumPy, Pandas, and Scikit-learn.

The skill gap in the industry is significant, with many companies struggling to find data scientists with the necessary skills and knowledge. Participants in this program will be well-prepared to take on a variety of roles, from data analyst to data scientist, and will have a strong foundation for a successful career in data science. In Aurora, IL, companies such as Caterpillar, Navistar, and the City of Aurora are looking for skilled data scientists to help drive their businesses forward.

With this certification, participants will have a wide range of career opportunities available to them.

Customer Testimonials

Hear from our successful graduates

★ ★ ★ ★ ★

Great class, very informative.

James Conklin

Project Manager, Harris Health System

★ ★ ★ ★ ★

Great PMP® Bootcamp. I had a great time taking this course. I took the course to prepare to sit for the CAPM® but may be able to sit for the PMP®. I learnt a lot was challenging. Great course. We need one more day. Content was very detailed.

Karle Scroggins

Operations Coordinator, Harris Health System

★ ★ ★ ★ ★

it was a great class. Lots of energy. And I enjoyed.

John Denke

Project Manager , Boeing

★ ★ ★ ★ ★

Fantastic course to prepare for PMP® exam.

Kevin Hambrice

Global Factory Sales & Marketing Manager, ABB

★ ★ ★ ★ ★

As a participant it was smooth sailing for me.

Eric S. Tumlinson

Sr. Project Manager, Montco Oilfield Contractors, LLC

★ ★ ★ ★ ★

Trainer was excellent. Shared good resources and good experiences.

Khemoni Holmes

Project Manager, Harris Health System

★ ★ ★ ★ ★

Good content and training.

Dennis Glover

Project Manager, eProtex

★ ★ ★ ★ ★

I wanted to let you know that I took and passed the PMP exam. Thanks to iCert Global and especially my Cincinnati course instructor, who was an excellent teacher and helped me immensely.

Steve Ditty

Executive Director, Cogent IBS

★ ★ ★ ★ ★

Trainer was good. Trainer was very engaged and interacting. Very much satisfied with the training.

Stefan Long

Owner, MAGMAX Group LLC

★ ★ ★ ★ ★

I was pleasantly surprised at the quality of this training. Yomi was awesome as a trainer and working to make sure that we understood the concepts. Controlling Cost and Controlling Risk are the most complicated, but Yomi spent time after class working through questions to help others understand. This class also helped to change my perception of the PMP being this MONSTER to something that I can I can successfully do.

Nancy Davis

Sr. Project Manager , GK Software USA, Inc

★ ★ ★ ★ ★

Great class with a lot of information and tips to prepare for the exam

John Eric Nelson

Business Development Manager , WCA Waste

★ ★ ★ ★ ★

It was a great course, covered all the things that i ended up hitting road bumps on. I was the only one in the class, but the trainer was just as involved as if it had been a full class.

Mark Butler

Project Manager, Starbucks Via Aerotek

★ ★ ★ ★ ★

I was nervous about taking it online versus classroom; but I am actually glad I took it online. Instructor was very great and gave a good learning experience with his relevant project management experience.

Xeng Yang

IT Specialist, Beautiful Creations & More

★ ★ ★ ★ ★

The training was very intense but covered with course material. It was more than I expected.

Bernadette Gilliam

Operations/Technical Support Analyst , The Johns Hopkins Hospital

★ ★ ★ ★ ★

I thought the class was very informative. The instructor did an excellent job breaking down each chapter to where it was easy to understand. I was also very impressed with his commitment to help us pass ever after the class is over.

Taylor Mitchell

Business Management, AT&T

★ ★ ★ ★ ★

Excellent training. Instructor was very knowledgeable and explained information in an understandable way

Sandra Hamilton Allen

Sales Analyst , Alcon

★ ★ ★ ★ ★

Quality Materials presented, Instructor very knowledgeable. Exceeded my expectations.

Anthony Muldrow

Engineering Safety Manager, SNC-Lavalin

★ ★ ★ ★ ★

The training is a great introduction into the PMI mindset. Very informative and helpful

Bryan Tamburro

Managing Partner, Arrakis Development LLC

Course & Support

Everything you need to know about our training options and support

How long does the training take to complete? ▾

The program is delivered over an intensive, structured 6-week period. This provides the necessary pace for deep statistical concept assimilation and hands-on Python coding practice.

What are the different training formats available? ▾

We offer three options for our Data Science with Python course: E-Learning for ultimate self-pacing, Instructor-Led Live Classes for real-time interaction, and Classroom Training in metros like Aurora, IL for an immersive, focused environment.

Are the classes fully interactive or just passive lectures? ▾

Our LIVE sessions are fully interactive, with mandatory Python coding exercises, Q&A, and live debugging sessions where you share your screen and work through errors with the instructor.

What Python software or tools do I need to install? ▾

You only need to install Python and Jupyter Notebooks/Anaconda (all free). Our instructors guide you through the setup and package installation in the first module.

What if I miss a scheduled live class session? ▾

Every single session is recorded in high-quality video and uploaded within 24 hours. You also have the flexibility to attend the missed session in any other running batch at no extra charge.

Who are the instructors? ▾

Our instructors are senior Data Scientists and Analytics Consultants with 8+ years of experience, holding advanced degrees and actively building predictive models for enterprise clients using Python.

What is the average class size for the live sessions? ▾

We cap all live online sessions at 25 participants to ensure every student receives personalized Python code review, direct statistical coaching, and ample time for Q&A.

Is there a difference between the weekend and weekday batches? ▾

No. The curriculum, Python code assignments, instructor expertise, and statistical rigor are identical. The only difference is the schedule pacing to fit your professional life.

Do I need access to any paid data sources or libraries? ▾

No. We utilize publicly available, industry-standard datasets and only use free, open-source Python packages (Pandas, Scikit-learn). Your only expense is the course fee and the exam fee.

Is this training valid for candidates outside Aurora, IL? ▾

Yes. The principles of Data Science, Python programming, and statistical modeling are global standards. Our Data Science with Python certification online classes are accessible worldwide.

Data Science with Python Training in Other Cities

Arlington Heights, IL Aurora, IL Bartlett, IL Belleville, IL Berwyn, IL Bloomington, IL Bolingbrook, IL Buffalo Grove, IL Carol Stream, IL Champaign, IL Chicago, IL Cicero, IL Crystal Lake, IL Decatur, IL DeKalb, IL Des Plaines, IL Downers Grove, IL Elgin, IL Elmhurst, IL Evanston, IL Glenview, IL Hoffman Estates, IL Joliet, IL Lombard, IL Moline, IL Mount Prospect, IL Naperville, IL Normal, IL Oak Lawn, IL Oak Park, IL Orland Park, IL Palatine, IL Peoria, IL Plainfield, IL Quincy, IL Rockford, IL Romeoville, IL Schaumburg, IL Skokie, IL Springfield, IL Streamwood, IL Tinley Park, IL Urbana, IL Waukegan, IL Wheaton, IL Wheeling, IL