Python for Data Science Immersive

at Practical Programming - Midtown

(378)
Course Details
Price:
$1,495 30 seats left
Start Date:

Mon, Jul 11, 10:00am - Jul 15, 5:00pm Eastern Time (5 sessions)

Next start dates (2)

Location:
Midtown, Manhattan
185 Madison Ave 3rd Fl
34th & Madison
New York, New York 10016
(Map)
Purchase Options
Description
Class Level: Beginner
Age Requirements: 18 and older
Average Class Size: 5

Flexible Reschedule Policy: This provider has flexible, free rescheduling for any-in person workshop. Please see the cancellation policy for more details

What you'll learn in this data science course:

Python for Data Science [Online and Onsite]

Data Science Immersive® is a week-long comprehensive course with an emphasis on the practical application of Python to data analysis. Initially developed for Wall Street professionals, Python for Data Science Immersive® quickly became popular among people who crunch numbers, analyze big-data and simply want to switch from spreadsheets to faster and more efficient Python programming language.

Data Science Immersive is a week-long 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 Syllabus


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 loops
  • Indexing and slicing
  • Reading data from CSV and TXT Files
  • Writing to CSV and TXT Files
  • Analyzing 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

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
  • High-performance Pandas: Eval and Query
  • Hierarchical indexing
  • Handling missing data
  • Python Data Analysis Library - Pandas
  • Pandas data structures
  • Practical exercises

Day5

  • Web scraping and Data Mining
  • Visualization with Matplotlib
  • Line Plots, Scatter Plots and Histograms
  • Customizing Plots
  • Multiple Subplots
  • Density and Contour Plots
  • Python best practices
  • How to write fast and efficient code – Big-O notation
  • Q&A

Still have questions? Ask the community.

Refund Policy
If you withdraw two days before the course start date, any deposit paid will be refunded in full. 

No refunds will be given for cancellations made after that date. If you cannot attend our class or workshop, for which you were charged, you will receive 25% discount for any other course.

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Practical Programming

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Start Dates (3)
Start Date Time Teacher # Sessions Price
10:00am - 5:00pm Eastern Time TBD 5 $1,495
This course consists of multiple sessions, view schedule for sessions.
Tue, Jul 12 10:00am - 5:00pm Eastern Time TBD
Wed, Jul 13 10:00am - 5:00pm Eastern Time TBD
Thu, Jul 14 10:00am - 5:00pm Eastern Time TBD
Fri, Jul 15 10:00am - 5:00pm Eastern Time TBD
10:00am - 5:00pm Eastern Time TBD 5 $1,495
This course consists of multiple sessions, view schedule for sessions.
Tue, Sep 13 10:00am - 5:00pm Eastern Time TBD
Wed, Sep 14 10:00am - 5:00pm Eastern Time TBD
Thu, Sep 15 10:00am - 5:00pm Eastern Time TBD
Fri, Sep 16 10:00am - 5:00pm Eastern Time TBD
10:00am - 5:00pm Eastern Time TBD 5 $1,495
This course consists of multiple sessions, view schedule for sessions.
Tue, Nov 01 10:00am - 5:00pm Eastern Time TBD
Wed, Nov 02 10:00am - 5:00pm Eastern Time TBD
Thu, Nov 03 10:00am - 5:00pm Eastern Time TBD
Fri, Nov 04 10:00am - 5:00pm Eastern Time TBD

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Reviews of Classes at Practical Programming (378)

(378 Reviews)
Python for Data Science Immersive
Reviewed by Anonymous on 3/21/2020
Very instructive course. Definitely worthwhile if you are trying to learn Python. The teacher was engaging and was able to cater to different levels of expertise among the attendees.
Python for Data Science Immersive
Reviewed by Anonymous on 12/16/2019
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