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Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873)

4.6 out of 5 rating Last updated 13/12/2024   English

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Global Schedule

GTR = Guaranteed to Run

29 Jan 25 Book
15:00 - 23:00 Live Online 1,995
05 Mar 25 Book
15:00 - 23:00 Live Online 1,995

14 May 25 Book
15:00 - 23:00 Live Online 1,995
16 Jul 25 Book
15:00 - 23:00 Live Online 1,995
10 Sep 25 Book
15:00 - 23:00 Live Online 1,995
12 Nov 25 Book
15:00 - 23:00 Live Online 1,995
10 Dec 25 Book
15:00 - 23:00 Live Online 1,995
Duration

3 Days

18 CPD hours

Overview

Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore:
- Understand Python's Core Topics: Gain a firm grasp of fundamental Python concepts such as flow control, sequences, arrays, dictionaries, and file handling. This understanding forms the cornerstone of your Python programming journey.
- Navigate Key Python Libraries: Develop proficiency in leveraging the power of Python's primary libraries, numpy and pandas. By the end of the course, you'll be confidently transforming, reshaping data, and handling large number sets.
- Generate Insightful Visualizations: Learn how to create meaningful and visually appealing data visualizations using matplotlib. These skills will enable you to better communicate data-driven insights.
- Efficient Data Handling: Acquire techniques to optimize your data handling processes, enhancing productivity and making your workflow more efficient.
- Manage Errors Effectively: Become proficient in handling common challenges like syntax errors and exceptions, enhancing the reliability and robustness of your Python code.
- Hands-on Experience with Web Notebooks: Gain practical experience using interactive web notebooks like iPython, Jupyter, and Zeppelin. These tools offer a dynamic platform for writing, testing, and debugging your Python code, enriching your learning experience.

Description

Fast Track to Python for Data Science and/or Machine Learning is a three-day, hands-on course geared to equip you with the knowledge and skills necessary to handle various data science projects efficiently using Python, one of the most popular languages in the industry. Python's ease of use, extensive libraries, and robust community make it a fantastic choice for professionals seeking to enhance their data science capabilities. From automating small tasks to building complex data models, Python can enable you to streamline your work or provide significant insights for your organization.
Working in a hands-on learning environment led by our expert instructor, you'll also gain experience with Python's core topics like flow control, sequences, arrays, dictionaries, and handling files. You'll delve into functions, sorting, essential demos, the standard library, and even dates and times. You'll learn how to manage syntax errors and exceptions effectively, enhancing your code's resilience and your productivity. You'll delve into how Python it operates within web notebooks such as iPython, Jupyter, and Zeppelin, where you'll practice writing, testing, and debugging your Python code.
You'll also gain practical experience with Python and key data science libraries, enabling you to optimize data handling and create insightful visualizations. You'll explore working with large number sets and transforming data in numpy, reading, writing, and reshaping data with pandas, and creating data visualizations with matplotlib. You'll also gain experience optimizing data handling processes, creating insightful visualizations, or making data-driven decisions.
By the end of this journey, you'll have a solid understanding of Python for data science, including data analysis, manipulation, and visualization, ready to apply these new skills in your work. This course aims not just to teach Python but also to lay a strong foundation for you to continue building upon, enhancing your proficiency in Data Science and enabling you to contribute effectively to your team's data projects.

Prerequisites

This course is geared for data analysts, developers, engineers or anyone tasked with utilizing Python for data analytics tasks. While
there are no specific programming prerequisites, students should be comfortable working with files and folders and should not be
afraid of the command line and basic scripting.

An Overview of Python
Why Python
Python in the Shell
Python in Web Notebooks (iPython, Jupyter, Zeppelin)
Demo: Python, Notebooks, and Data Science
Getting Started
Using variables
Builtin functions
Strings
Numbers
Converting among types
Writing to the screen
Command line parameters
Running standalone scripts under Unix and Windows
Flow Control
About flow control
White space
Conditional expressions
Relational and Boolean operators
While loops
Alternate loop exits
Sequences, Arrays, Dictionaries and Sets
About sequences
Lists and list methods
Tuples
Indexing and slicing
Iterating through a sequence
Sequence functions, keywords, and operators
List comprehensions
Generator Expressions
Nested sequences
Working with Dictionaries
Working with Sets
Working with files
File overview
Opening a text file
Reading a text file
Writing to a text file
Reading and writing raw (binary) data
Functions
Defining functions
Parameters
Global and local scope
Nested functions
Returning values
Sorting
The sorted() function
Alternate keys
Lambda functions
Sorting collections
Using operator.itemgetter()
Reverse sorting
Errors and Exception Handling
Syntax errors
Exceptions
Using try/catch/else/finally
Handling multiple exceptions
Ignoring exceptions
Essential Demos
Importing Modules
Classes
Regular Expressions
The standard library
Math functions
The string module
Dates and times
Working with dates and times
Translating timestamps
Parsing dates from text
Formatting dates
Calendar data
numpy
numpy basics
Creating arrays
Indexing and slicing
Large number sets
Transforming data
Advanced tricks
Python and Data Science
Data Science Essentials
Working with Python in Data Science
Working with Pandas
pandas overview
Dataframes
Reading and writing data
Data alignment and reshaping
Fancy indexing and slicing
Merging and joining data sets
Time Permitting

matplotlib
Creating a basic plot
Commonly used plots
Ad hoc data visualization
Advanced usage
Exporting images
Additional course details:

Nexus Humans Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward.

This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts.

Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.

While we feel this is the best course for the ITS Data Analytics course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.

Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

FAQ for the Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) Course

Available Delivery Options for the Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) training.
  • Live Instructor Led Classroom Online (Live Online)
  • Traditional Instructor Led Classroom (TILT/ILT)
  • Delivery at your offices in London or anywhere in the UK
  • Private dedicated course as works for your staff.
How many CPD hours does the Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) training provide?

The 3 day. Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) training course give you up to 18 CPD hours/structured learning hours. If you need a letter or certificate in a particular format for your association, organisation or professional body please just ask.

Which exam does the Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) training course prepare you for?

The Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) prepares you for the Yes official exam. You can take this exam at any exam center across Ireland including, Dublin, Cork, Galway, Northern Ireland or live online where ever you are. Exams vary in duration and if required you can request with the provider for any accommodations appropriate for you.

What is the correct audience for the Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) training?

This introductory-level is for data analysts, engineers or anyone new to Python, tasked with utilizing Python for data analytics tasks.

Do you provide training for the Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873).

Yes we provide corporate training, dedicated training and closed classes for the Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873). This can take place anywhere in Ireland including, Dublin, Cork, Galway, Northern Ireland or live online allowing you to have your teams from across Ireland or further afield to attend a single training event saving travel and delivery expenses.

What is the duration of the Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) program.

The Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) training takes place over 3 day(s), with each day lasting approximately 8 hours including small and lunch breaks to ensure that the delegates get the most out of the day.

What other terms do people search for when looking for this course?

Popular related searched include Python; Data Science; Data Anlaysis; Machine Learning.

Why are Nexus Human the best provider for the Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873)?
Nexus Human are recognised as one of the best training companies as they and their trainers have won and hold many awards and titles including having previously won the Small Firms Best Trainer award, national training partner of the year for Ireland on multiple occasions, having trainers in the global top 30 instructor awards in 2012, 2019 and 2021. Nexus Human has also been nominated for the Tech Excellence awards multiple times. Learning Performance institute (LPI) external training provider sponsor 2024.
Is there a discount code for the Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) training.

Yes, the discount code PENPAL5 is currently available for the Fast Track to Python for Data Science | Python Essentials, Data Science Libraries, Pandas, Numpy & More (TTPS4873) training. Other discount codes may also be available but only one discount code or special offer can be used for each booking. This discount code is available for companies and individuals.

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Training Insurance Included!

When you organise training, we understand that there is a risk that some people may fall ill, become unavailable. To mitigate the risk we include training insurance for each delegate enrolled on our public schedule, they are welcome to sit on the same Public class within 6 months at no charge, if the case arises.

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