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Data Science Immersive Weekend

Practical Programming

4.5 330 reviews

Beginner
15 and older
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29 E Madison, 16 Fl., Chicago, IL
32 hours over 4 sessions

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Description

Data Science Immersive is 4 session comprehensive course with an emphasis on the practical application of Python to data analysis. In the first two days we cover Python's built-in data types, explaining differences in the behavior of data structures, laying a foundation for the more complex NumPy and Pandas structures.

A deep understanding of data types prepares users to solve real-life challenges with the right tools in the most efficient manner. Also, it is important to understand why some of the types are faster and some are just an extension of others.

In this course we are not covering in-depth mathematical and statistical concepts, rather we master practical usage of the Python programming language and its extensions NumPy and Pandas.

During this course we solve many real-world financial, statistical, and analytical problems. We are always open to new challenges and asking aspiring programmers to bring their projects so we could solve them together.

When you sign up for this course, you should also be prepared to work hard.  While we do explain all of the concepts thoroughly and have notes on each lesson that you can refer back to, we follow up each lesson with practice problems to reinforce the material.  We code almost seven hours a day with breaks for lunch and coffee.

At the end of this course, you will have a fundamental understanding of the Python programming language and its analytical libraries: NumPy, Pandas, and Matplotlib. You will learn the best practices and understand how to write clean and efficient Python code.  Also, you will gain essential knowledge of data structures needed to solve financial, analytical, and statistical problems in a fast and efficient manner.

Moreover, you will have a portfolio of sample code solutions done in a professional style.

Data Science Immersive

Day 1

Variables
Built-in data types: strings, integers, floats, lists
Introduction to built-in functions
Behavior of Data Structures
Control flow statementsIf, Elif, Else statements
Definite loops: For loopsPractical exercises

Day 2

How to write custom Python functions
Built-In data types: tuples, dictionaries, sets
Indefinite loops: While loopsIndexing and slicing
Reading data from CSV and TXT Files
Writing to CSV and TXT FilesAnalyzing a file’s content
Practical exercises

Day 3

Lambda
List comprehensions
Scientific computing with Python
NumPy arrays
Creating and manipulating NumPy arrays
Computation on NumPy arrays
Broadcasting and UFuncs
Sorting and Indexing NumPy arrays
Pandas Library for Data Analysis
Series and DataFrame
Gathering and Cleaning data

Day 4

Aggregating data in Pandas
Data Indexing and Selection
Logic, Control Flow and Filtering in Pandas
Grouping by for analytics
Combining datasets and Merging datasets
Hierarchical indexing
Handling missing data
Visualization with Matplotlib
Line Plots, Scatter Plots and Histograms
Q&A

Refund Policy

To reschedule or cancel, email us at [email protected]

All courses include a non-refundable registration fee (10% of the undiscounted course price).

Students may cancel up to 11 business days before the class/program start date and receive a refund, less the registration fee.
Cancellations within 11 business days are not permitted; however, students may reschedule up to 4 business days before the class start date.

Note: Any refunds must be requested within 180 days from the original payment date; courses rescheduled within 11 business days of the start date are not eligible for refunds.

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(4.5-star rating across 330 reviews)

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Practical Programming

Practical Programming offers programming classes and workshops for individuals of all skill levels who are interested in learning Python coding. It is suitable for beginners and those looking to start a career in programming or build dynamic web applications using Python.

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