Advanced Python - eLearning Bundle Course



Course Details:

Length: 7 courses

Access Length: 6 months

Price: $900/person (USD)

Bulk Pricing: 10+ Contact Us

Course Features:

Instant Access After Purchase

Lecture by Recorded Video

Stop and Start as Needed

Certificate of Completion

Software Lab Included?: No

Delivery Method:

Self-Paced Online

Individuals and Groups
@ Your Location

 


Course Overview

Unleash the Power of Data and AI with the Ultimate Master Bundle!

Do you want to master algorithms that optimize performance, wrangle messy data into actionable insights, and build cutting-edge AI systems? This master bundle combines three powerhouse courses to turn you into a data and AI powerhouse!

Level Up Your Algorithmic Toolkit:

  • Advanced Data Structures and Algorithms in Python: Master the building blocks of efficient code, crafting complex, reusable algorithms in Python. Optimize speed, tackle challenging problems, and unlock the true potential of your applications.

Conquer Data Chaos with Python:

  • Data Wrangling with Python 3.x: Transform raw data into valuable insights. Learn practical techniques to clean, analyze, and visualize real-world datasets, even those filled with anomalies. Become a data wrangling champion with Python!

Build Intelligent Automation with Deep Learning:

  • Deep Learning for Python Developers: No more math degrees required! Build AI systems with Deep Learning, even if you're a Python newbie. Master neural networks and frameworks like TensorFlow and Keras, and craft intelligent solutions for speech recognition, image analysis, and more!

This Master Bundle offers:

  • 10+ hours of hands-on learning: Dive deep into practical skills and real-world projects.
  • Coding mastery in Python: Unleash the power of Python for algorithms, data wrangling, and Deep Learning.
  • Career-boosting skills: Become a sought-after developer with in-demand data and AI expertise.
  • Confidence to tackle any challenge: Master complex algorithms, wrangle messy data, and build cutting-edge AI systems.

Invest in your future. Enroll in the Master Bundle today and unlock the power of data and AI!

Also Included - 4 Courses: An Essential Career Skills Pack with 4 courses in key areas for career management and growth, including Time Management, Digital Skills, Creativity and Soft Skills.

 


Course Notes


Important Course Information
This is a Lecture-Only eLearning Course. If you would like to practice any hands-on activities, you must use your own software.

eLearning Training Delivery Method


How It Works

This self-paced online course lets you learn independently at your own pace through Certstaffix Training's easy-to-use platform.

  • Learn at your own pace - Start and stop as it is convenient for you. Pick up where you left off.
  • Lecture utilizing video and recorded screenshots
  • 6-month subscription length
  • Instant Access After Purchase

Have more than 10 students needing this course? Contact Us for bulk pricing.

Target Audience:
  • Python Developers: Enhance your coding skills with advanced algorithms, data manipulation techniques, and AI integration.
  • Data Analysts & Scientists: Expand your data-wrangling capabilities and explore Deep Learning for AI-powered analysis.
  • Software Engineers: Optimize code performance and explore new AI-driven development opportunities.
  • Aspiring AI Practitioners: Build a solid foundation in Deep Learning without extensive math prerequisites.
  • Career Changers: Break into the exciting fields of data science and AI with hands-on learning.
  • Anyone Curious About Data and AI: Develop valuable skills in high-demand fields, regardless of your background.
Key Features
  • Audio Narration
  • Video
  • Inline Activities
  • Supplemental Resources
Languages
  • Audio/Video/Course Text: American English.
  • Subtitles (Closed Caption): N/A.
Course Duration
  • Advanced Python Bundle: 9 hrs 57 min
  • Essential Career Skills Pack: 2 hrs 23 min

 


Course Topics

Advanced Data Structures and Algorithms in Python

Course Duration - 4 hrs 11 min

As a developer, you will have undoubtedly heard about various data structures and algorithms. However, have you ever thought profoundly about them and their impact on the performance of your applications? If not, it’s high time to look at this topic, and this course is a one-stop guide to master it! This course will teach you the necessary theory and applications to properly understand the advanced algorithms and data structures critical to various problems and how to implement them. We’ll also go hands-on and reveal tips and tricks for optimizations, identifying suitable approaches, and presenting convincing explanations. And you will get it all in a modern, popular, well-documented language: Python. Finally, you will learn how to develop complex, easy-to-understand, debug, and reusable algorithms in various applications.

By the end of the course, you will know how to develop complex algorithms that are easy to understand, debug, and reusable in various applications.

Course Objectives:
Course Objectives:
  • Analyze the time and space complexity of complex algorithms: Understand how different algorithms impact program performance and choose the most efficient approach for specific problems.
  • Master advanced data structures like segment trees, treaps, and binary indexed trees: Leverage these structures to solve complex problems efficiently and optimize solutions.
  • Implement dynamic programming for optimal solutions: Master the divide-and-conquer approach and apply it to solve optimization problems like shortest path and minimum cost path.
  • Design and develop reusable algorithms in Python: Gain the skills to create modular and adaptable algorithms applicable in various application contexts.
  • Optimize algorithms for improved performance: Explore techniques like lazy updates and caching to enhance algorithm efficiency and speed.
  • Apply advanced math concepts like the inclusion-exclusion principle to solve problems: Gain confidence in using mathematical foundations to tackle algorithmic challenges.
  • Develop algorithms with clarity and debuggability: Learn coding practices for creating easy-to-understand and maintainable algorithms.
  • Tackle diverse algorithmic problems using appropriate data structures and techniques: Gain the flexibility to apply your knowledge to a wide range of problem domains.
  • Master popular algorithms like Manacher's algorithm and Held-Karp algorithm: Learn specific solutions to critical problems in areas like palindrome detection and traveling salesman optimization.
  • Deepen your understanding of recursive algorithms and their applications: Master recursion, a fundamental algorithmic concept, and apply it to solve problems like Towers of Hanoi and arithmetic expression evaluation.
Detailed Course Outline:
Detailed Course Outline:
Doing a Lot With Very Little
  • The Course Overview
  • From Painfully Slow to Optimal: The Maximum Sum Subarray
  • Find the Factorial with a Given Number of Zeros
  • Find the Given-Length Subarray with the Maximum Minimum
  • Array Problems Involving Modulos
  • Useful Math: The Inclusion-Exclusion Principle
More Complex Algorithms on Arrays
  • Rolling Hashes for Constructing a Palindrome
  • Efficiently Counting Subarrays with a Given Sum
  • Binary Searching for an Optimal Subarray Length
  • Manacher’s Algorithm
  • Optimizing the Sieve of Eratosthenes
General Recursive Algorithms
  • The Towers of Hanoi with Four Pegs
  • Evaluating Arithmetic Expressions with a Recursive Descent Parser
  • Matrix Exponentiation and Fibonacci-Like Functions
  • A Sum of Powers
  • Finding a Permutation with a Given Property
Dynamic Programming
  • What Is DP?
  • The Minimum Sum Path in a Matrix
  • A More Complex Minimum Sum Path in a Matrix
  • Counting the Number of Ways to Paint a Fence
  • Counting Increasing Subsequences
Advanced Dynamic Programming
  • Counting Digit Sums Divisible by d
  • Range Minimum Queries with DP
  • Another Matrix Path Problem
  • Dynamic Programming on Trees
  • TSP and the Held-Karp Algorithm
Tree-Based Data Structures
  • Segment Trees and the RMQ Problem
  • Segment Trees with Lazy Updates
  • Binary Indexed Trees
  • Binary Indexed Trees for the RMQ Problem
  • Treaps
Graph Theory Algorithms
  • The Lowest Common Ancestor
  • The Shortest Path and Back


 

Data Wrangling with Python 3.x

Course Duration - 3 hrs 35 min

You might be working in an organization or have your own business, where data is being generated continuously (structured or unstructured), and you are looking to develop your skillset to jump into the field of Data Science. This hands-on guide shows programmers how to process information. In this course, you will gather data, prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, and more! This course will equip you with the tools and technologies you need to analyze datasets (real-life datasets containing lots of anomalies) using Python so that you can confidently jump into the field and enhance your skill set. The best part of this course is the take-away code templates generated using the real-life dataset. Toward the end of the course, you will build an intuitive understanding of all the aspects available in Python for Data Wrangling.

Course Objectives:
Course Objectives:
  • Master data acquisition: Learn how to import and parse data from various sources like CSV, JSON, public web scraping, Excel, and PDF files, preparing it for analysis.
  • Understand database storage: Gain knowledge of relational and non-relational databases, comparing their suitability and implementing data storage in SQLite, MongoDB, and Elasticsearch.
  • Become a data cleaning expert: Develop skills to clean structured data effectively, including viewing/inspecting, renaming/adding/removing columns, dropping duplicates, indexing, merging/concatenating/joining data frames, and handling missing values.
  • Transform data for analysis: Master advanced data cleaning techniques like filtering/sorting data frames, encoding/mapping existing values, rescaling/standardizing columns, and exporting datasets for future use.
  • Perform statistical analysis with Python: Utilize libraries like Pandas, NumPy, SciPy, and Matplotlib to understand data characteristics, identify patterns, and perform descriptive statistical analysis.
  • Craft compelling data visualizations: Learn the power of visualizations to tell a story from your data, exploring cool examples and creating impactful visuals in Python using various tools.
  • Gain confidence in real-life datasets: Develop skills to handle messy, anomaly-filled datasets, equipping you for real-world data-wrangling challenges.
  • Build code templates for future use: Benefit from take-away code templates generated using real-life datasets, accelerating your future data-wrangling projects.
  • Deepen your Python knowledge: Expand your Python skills in the context of data manipulation, enhancing your overall programming expertise.
  • Gain a comprehensive understanding of data wrangling with Python: By tackling different aspects of data acquisition, cleaning, transformation, analysis, and visualization, you'll acquire a well-rounded foundation in data wrangling using Python.
Detailed Course Outline:
Detailed Course Outline:
Gathering and Parsing Data
  • Installing Anaconda Navigator on Windows/Linux
  • Importing and Parsing CSV in Python
  • Importing and Parsing JSON in Python
  • Scraping Data from Public Web (Parts 1 & 2)
Working with Data from Excel and PDF Files
  • Importing and Parsing Excel Files (Parts 1 & 2)
  • Manipulating PDF Files in Python (Parts 1 & 2)
Storing Data in Persistent Storage
  • Difference between Relational and Non-Relational Databases
  • Storing Data in SQLite Databases
  • Storing Data in MongoDB
  • Storing Data in Elasticsearch
  • Comparative Study of Databases for Storage
Cleaning Structured Data
  • The Importance of Data Cleaning
  • Viewing/Inspecting DataFrames
  • Renaming/Adding/Removing Columns
  • Dropping Duplicate Rows
  • Indexing DataFrames
  • Merging/Concatenating/Joining DataFrames
  • Dealing with Missing Values
More Data Cleaning and Transformation
  • Filtering and Sorting DataFrames
  • Encoding/Mapping Existing Values (Parts 1 & 2)
  • Rescaling/Standardizing Column Values
  • Common Cleaning Operations
  • Exporting Datasets for Future Use
Performing Statistical Analysis
  • Uses of Packages (Pandas, NumPy, SciPy, Matplotlib)
  • Types of Column Names/Features/Attributes
  • Split-Apply-Combine Operations
  • Descriptive Statistics in Python (Parts 1 & 2)
Let the Visualizations Tell the Story
  • Using Visualizations
  • Cool Visualization Examples
  • Visualizations in Python (Parts 1 & 2)
  • Exploring RAWGraphs Visualization Tool


 

Deep Learning for Python Developers

Course Duration - 2 hrs 11 min

Deep Learning is a new superpower that will let you build AI systems that weren't possible a few years ago. It's time to utilize intelligent automation to help your business grow, keep organized, and stay on top of the competition.

This course is for Python developers who haven't worked with machine learning or data science and want to build intelligent systems right away - without taking a math degree! You will learn about recurrent neural networks, Backprop, SGD, and more. You will work on code examples that are used in a developer's life daily; you will not only master the theory, but you will also see how to apply it in the industry as a whole. You will practice all these ideas in MxNet, TensorFlow, Keras, and Gluon. Last but not least, build Convolutional Neural Networks and apply them to image data.

Deep Learning enables numerous exciting applications in speech recognition, music synthesis, machine translation, natural language understanding, and many others. AI is transforming multiple industries. After finishing this course, you will likely find creative ways to apply it to your work. We will help you master deep Learning, understand how to apply it and build a career in AI.

Course Objectives:
Course Objectives:
  • Build intelligent systems with Deep Learning: Master the basic concepts and practical applications of Deep Learning without diving into heavy math, opening doors to AI system development.
  • Go beyond theory with practical coding: Gain hands-on experience by working on code examples relevant to your daily developer life, solidifying your understanding through real-world application.
  • Apply Deep Learning in diverse frameworks: Learn to implement Deep Learning models in popular frameworks like MxNet, TensorFlow, Keras, and Gluon, expanding your toolkit and flexibility.
  • Master crucial Deep Learning concepts: Gain in-depth knowledge of key topics like recurrent neural networks, Backpropagation, Stochastic Gradient Descent, and others, forming a strong foundation for your Deep Learning journey.
  • Tackle image data with Convolutional Neural Networks: Develop the skills to build and train CNNs, unlocking their potential for image recognition and analysis tasks.
  • Explore exciting Deep Learning applications: Discover the possibilities of Deep Learning in various fields like speech recognition, music synthesis, machine translation, and natural language understanding.
  • Optimize neural networks for improved performance: Learn techniques like weight initialization, regularization, and gradient normalization to enhance your Deep Learning models' efficiency and accuracy.
  • Master advanced optimization algorithms: Understand and implement adaptive learning algorithms like RMSProp and Adam for optimized model training and performance.
  • Fine-tune your models with hyperparameter tuning: Learn how to effectively adjust hyperparameters through Grid Search and Random Search methods, maximizing your model's potential.
  • Apply Deep Learning skills to real-world projects: Gain practical experience through mini-projects involving CIFAR classification, SIGNS dataset analysis, language modeling, and music synthesis, solidifying your ability to integrate Deep Learning into your work.
Detailed Course Outline:
Detailed Course Outline:
Getting Started with Deep Learning
  • Fundamentals of Neural Networks
  • Training Deep Neural Networks
  • Using Forward Propagation, Backprop, and SGD
  • Logistic Regression with a Neural Network Mindset
  • Convolutional Neural Network Handwriting Recognition
Deep Models with MXNet and TensorFlow
  • Working with MxNet and Gluon
  • Defining and Training Neural Networks in MxNet/Gluon
  • Working with TensorFlow and Keras
  • Defining and Training Neural Networks in Keras/TensorFlow
  • Comparing the Two Frameworks
  • Mini Project - CIFAR Classification
Improving Deep Neural Networks
  • Weight Initialization for Deep Networks
  • Regularization and Dropout
  • Normalizing and Vanishing/Exploding Gradients
  • Mini Project - SIGNS Dataset
Optimization Algorithms
  • Understanding Stochastic Gradient Descent
  • Adaptive Learning Algorithms - RMSProp and Adam
  • Mini Project - Language Modeling
Hyperparameter Tuning
  • Hyperparameters
  • Tuning Hyperparameters - Grid Search
  • Tuning Hyperparameters - Random Search
  • Mini Project - Music Synthesis

 


 


Essential Career Skills Pack


Productivity and Time Management

Course Duration - 30 min

It seems that there is never enough time in the day. But, since we all get the same 24 hours, why is it that some people achieve so much more with their time than others? This course will explain how to plan and prioritize tasks, so that we can make the most of the limited time we have. By using the time-management techniques in this course, you can improve your ability to function more effectively – even when time is tight and pressures are high. So, by the end of the course you will have the knowledge, skills and confidence to be an effective manager of your time.

Course Objectives:
Course Objectives:
  • Set your priorities to better manage your time
  • Improve your productivity by sharpening your focus and multitasking effectively
Detailed Course Outline:
Detailed Course Outline:
  • Productiity & Time Management
  • Prioritization
  • Getting Things Done
  • Procrastination
  • Multitasking & Focus
  • Summary


 

Basic Digital Skills

Course Duration - 13 min

With the rise of digital transformation and technology, having a basic digital literacy is essential for all types of jobs, regardless of the industry. To stay competitive and be successful in the workplace, enhancing your digital skills should be a top priority.

Course Objectives:
Course Objectives:
  • Recall the essential digital skills framework
  • Elaborate on the toolkit of essential digital skills
  • Identify how to develop or improve your digital skills
Detailed Course Outline:
Detailed Course Outline:
  • The Essential Digital Skills Framework
  • The Toolkit of Essential Digital Skills
  • Developing Digital Skills
  • Summary


 

4 Ways to Boost Creativity

Course Duration - 30 min

The digital economy is opening up ways for everyone to be creative. It doesn’t just mean being artistic – it’s more about ideas, solutions, alternatives, incremental improvements. Peter Quarry and Eve Ash discuss ways that mental capacity can be developed, perspectives changed, group power leveraged and making things actually happen.

Course Objectives:
Course Objectives:
  • Define creativity
  • Think outside the box
  • Develop the right mental attitude
  • Leverage the power of groups
  • Ensure managers make it happen
Detailed Course Outline:
Detailed Course Outline:
  • What is Creativity at Work?
  • Learn to Think Outside the box
  • Develop the Right Mental Capacity
  • Laverage the Power of Groups
  • Ensure Managers Make It Happen
  • Summary


 

The 11 Essential Career Soft Skills

Course Duration - 1 hr 10 min

Soft Skills are the traits, characteristics, habits, and skills needed to survive and thrive in the modern work world. Soft skills aren't usually taught in school, but you will learn them all here in this course. Are you someone that other people in your organization and industry like to work with, collaborate with and partner with? Are you seen as a valuable asset to any new project that comes along?

This soft skills training course will teach you how to develop the skills that can make the difference between a lackluster career that tops out at middle management versus one that lands you in the executive suite. Or to wherever you define career success. So many soft skills seem like common sense at first glance, but they are not commonly applied by most workers. This soft skills training course will give you an edge over your competitors. It will also make your job, your career and your life more rewarding and enjoyable.

Course Objectives:
Course Objectives:
  • Understand how to be a great communicator
  • Become a stronger listene
  • Appear professional to co-workers and bosses of all ages
  • Avoid common career blunders that often end careers
  • Manage expectations for bosses and colleagues
  • Position yourself for promotions
  • Make technology your asset, even if you are afraid of technology
  • Avoid the Not My Job Syndrome
  • Develop EQ to Match Your IQ
  • Develop leadership qualities
Detailed Course Outline:
Detailed Course Outline:
  • Introduction
  • The Soft Tech Savvy Way to Always Be Essential
  • Not My Job, And I Am Happy to Do It
  • You Can Become a Master Communicator
  • Feedback Video for The 11 Essential Career Soft Skills
  • Become a Leader Without the Title or Formal Authority
  • Your EQ Will Beat a Higher IQ
  • Building Your Winning Team
  • Make Every One of Your Seconds Count
  • Unleash Your Inner Anthony Robbins
  • Avoid Being Uncool
  • Clothes Can Still Make or Break Your Career
  • Conclusion The 11 Essential Career Soft Skills
  • Extra: Developing Your Career Secret Sauce

 



 


Related Python Information:

How Much Do Python Training Courses Cost?

Public instructor led Python training course prices start at $2,025 per student. Group training discounts are available.

Self-Paced Python eLearning courses cost $475 at the starting point per student. Group purchase discounts are available.

What Python Skills Should I Learn?

A: If you are wondering what Python programming skills are important to learn, we've written a Python Skills and Learning Guide that maps out Python skills that are key to master and which of our courses teaches each skill.

Read Our Python Skills and Learning Guide

Take Python Language Training

Are you thinking about honing your Python skills? Explore the best Python training online with Certstaffix Training. We offer three flexible ways to help you boost your proficiency in Python language training; our live Python online classes, self-paced eLearning, and corporate in-person courses.

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A: As one of the most ubiquitous and dynamic programming languages today, Python has inspired countless employees to learn to code. Novices can familiarize themselves with Python through self-instruction, enrolling in college, or signing up for training courses offered by private companies. Regardless of the educational resource chosen, students should commit at least 100 hours to programming practice before attempting certification exams. The particular courses that a student should sign up for can depend on their skill level, current or future professional duties, and whether they want to obtain a certification.

More Information on How to Learn Python and Get Certified

Is Python hard to learn?

A: Python is not a particularly difficult language to learn. In fact, many people find it much easier to pick up than other languages. The reason for this is that Python is designed to be very intuitive and easy to read. However, like any language, it does take some time and effort to master. The best way to learn Python is to attend a training course or class from a reputable provider. This will give you the chance to get hands-on experience with the language and also receive expert guidance from an experienced instructor.

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A: Python is a versatile language that you can use on the backend, frontend, or full stack of a web application. You can also use Python for data science and machine learning. The sky is the limit with what you can do with Python.

The answer to how long it will take you to learn python really depends on your level of experience and expertise with coding languages. If you are starting from scratch, it will obviously take longer than if you already have experience in coding.

You can learn Python in a few days with a formal training course or several weeks with online self-learning tutorials. Either way, continued practice after initial learning is key to grow and maintain your Python skills.

That being said, our Python classes at Certstaffix Training are designed to get you up to speed as quickly as possible. Our expert instructors will guide you through each concept, providing plenty of opportunity for practice and hands-on learning. Our Introduction to Python course is 4 days in length and is intended for those brand new to Python or with just some experience.

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A: If you're interested in learning Python, there are a few different options available to you. You can take classes online or in-person, and there are even some free resources available if you want to learn on your own.

The best way to learn Python will depend on your learning style and goals. If you're looking for a more structured learning experience, taking classes is probably the best option. On the other hand, if you're the type of person who likes to learn at their own pace, there are plenty of resources available online that can help you get started with python programming.

No matter what route you decide to take, starting off with some basic python tutorials is always a good idea. This will help you get a feel for the syntax and structure of the language before you start diving into more complex topics. Once you have a solid understanding of the basics, you can then start exploring python's many powerful features.

If you're ready to get started learning Python, there are plenty of great resources available to help you on your journey. Just remember to take things at your own pace, and don't be afraid to ask for help when you need it. With a little bit of effort, you'll be writing python code in no time.

Certstaffix Training offers Python eLearning and live instructor-led classes. Browse our Python training courses or contact us today to learn more.

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Learning a new programming language can be challenging, but it also opens up a world of possibilities and opportunities. Among the many languages available, Python stands out as one of the most versatile and widely used ones. Whether you are looking for in person classes or online training options, there is no shortage of options for a Python programming course near me.

In today's fast-paced business world, having a strong understanding of Python is practically essential. As such, it is crucial to find the best Python instructor led training available near me or online. This will ensure that you receive the highest quality education and are able to fully grasp the intricacies of this powerful language.

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What are the top Python skills?

A: Python is a versatile language that you can use for a wide variety of tasks. Whether you're a web developer, data analyst, artificial intelligence engineer, or anything in between, there's a good chance that Python can help you get the job done.

But what are the most important Python skills to have? Here are five of the most important Python skills that you should focus on honing:

Top Python Skills

1. Web Development - If you want to be a web developer, then you need to know how to use Python. Python is a popular language for web development, thanks to its ease of use and robust libraries. With Python, you can create everything from simple websites to complex web applications.

2. Data Analysis - Python is also a great language for data analysis. With its powerful libraries, Python makes it easy to work with large datasets and perform complex statistical analyses. If you want to be a data analyst, then you need to be proficient in Python.

3. Artificial Intelligence - Artificial intelligence is one of the hottest fields in tech right now, and Python is a great language for AI development. Python's libraries make it easy to work with data and build complex algorithms. If you want to be an AI engineer, then you need to know Python.

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5. Machine Learning - Machine learning is another hot area in tech, and Python is one of the best languages for machine learning development. With its powerful libraries and ease of use, Python makes it easy to build complex machine learning models. If you want to be a machine learning engineer, then you need to know Python.

These are just five of the most important Python skills that you should focus on honing. If you want to be a successful Python programmer, then you need to be proficient in all of these areas. So start learning Python today and master these essential skills.

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Python User Groups

Python Online Forums

Explore Python Training Classes Near Me:

Certstaffix Training provides Python classes near me or online, depending on the number of students involved. We offer online courses for individual learners, as well as in person classes at your office for corporate groups. Our trainers are highly experienced professionals with the expertise necessary to help you gain a thorough understanding of Python concepts and tools. With our courses available online for individuals or in person for corporate groups, it's easy to develop your Python skills. Start learning today and see how Certstaffix Training can help you reach your goals.







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