New - Gain Hands-on Experience using Python for Data Analytics | Intro to Python, Pandas, Numpy & More

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.

Who Should Attend?

This introductory-level technical course is geared for data analysts, developers, engineers or anyone new to Python, who are tasked with utilizing Python for data analytics tasks.

We can organize this training at your preferred date and location. Contact Us!

Prerequisites

This course is geared for technical users, so familiarity with basic scripting skills is recommended, as this course does not teach general scripting basics. Students should be comfortable working with files and folders as well as command line scripting.

What You Will Learn

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.

Training Outline

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
Nnumpy
- 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
Working with matplotlib
- Creating a basic plot
- Commonly used plots
- Ad hoc data visualization
- Advanced usage
- Exporting images

BONUS Day Four or Optional Topics

For Dedicated / Private Classes:

Leveraging AI for Python in Data Science

Introduction to AI with Python for Data Analysis
- Overview of AI Libraries
- Setting Up Your Environment:
- Understanding AI Models
- Creating Your First Model
- Evaluating Model Performance
Practical AI Projects in Python
- Set up a Python project for AI applications.
- Data Handling
- Model Development
- Test and validate your AI model's effectiveness.
- Applying Your Model
Using GPT Tools for Record Analysis in Data Science
- Introduction to GPT
- Setting Up GPT Tools
- Analyzing Text Data
- Generating Insights
- Practical Applications

Why Choose Us

Experience live, interactive learning from the comfort of your home or office with Bilginç IT Academy's Online Instructor-Led Fast Track to Python in Data Science Training in New Zealand. Engage directly with expert trainers in a virtual environment that mirrors the energy and schedule of a physical classroom.

Live Sessions: Join scheduled classes with a live instructor and other delegates in real-time.
Interactive Experience: Engage in group activities, hands-on labs, and direct Q&A sessions with your trainer and peers.
Global Expert Trainers: Learn from a handpicked global pool of expert trainers with deep industry experience.
Proven Expertise: Benefit from over 30 years of quality training experience, equipping you with lasting skills for success.
Scalable Delivery: Accessible worldwide, including New Zealand, with flexible scheduling to meet your professional needs.

Immerse yourself in our most sought-after learning style for Fast Track to Python in Data Science Training in New Zealand. Our hand-picked classroom venues in New Zealand offer an invaluable human touch, providing a focused and interactive environment for professional growth.

Highly Experienced Trainers: Boost your skills with trainers boasting 10-20+ years of real-world experience.
State-of-the-Art Venues: Learn in high-standard facilities designed to ensure a comfortable and distraction-free experience.
Small Class Sizes: Our limited class sizes foster meaningful discussions and a personalized learning journey.
Best Value: Achieve your certification with high-quality training and competitive pricing.

Streamline your organization's training requirements with Bilginc IT Academy’s Onsite Fast Track to Python in Data Science Training in New Zealand. Experience expert-led learning at your own business premises, tailored to your corporate goals.

Tailored Learning Experience: Customize the training content to fit your unique business projects or specific technical needs.
Maximize Training Budget: Eliminate travel and accommodation costs, focusing your entire budget on the training itself.
Team Building Opportunity: Enhance team bonding and collaboration through shared learning experiences in your workspace.
Progress Monitoring: Track and evaluate your employees' progression and performance with relative ease and direct oversight.

Why have you chosen us?

I have attended a training from Bilginc IT Academy before and I was satisfied.

I have attended a training from a different provider and it was not helpful.

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How many employees do you have in your IT department?

0 – 50

50 – 250

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Fast Track to Python in Data Science Training in New Zealand

Who Should Attend?

Prerequisites

What You Will Learn

Training Outline

Why Choose Us

Online Instructor-Led Training (VILT)

Classroom Based Learning

Onsite / In-House Learning

Available Training Dates