Python is a powerful and versatile programming language that's widely used in the world of data science and machine learning. In this Python for Beginners course, you will learn the fundamentals of Python programming, including data types, data structures, control flow, and more. By the end of the course, you will have a solid foundation in Python that will enable you to tackle more complex projects in the future. Learning outcomes: Understand the basic concepts of programming using Python Know how to install and set up a Python development environment Learn about data types and operators in Python Understand the various data structures available in Python Learn how to use control flow constructs in Python to make decisions and repeat actions Gain the ability to write simple Python programs from scratch Python for Beginners Part 1 is a comprehensive course designed for anyone who wants to learn the basics of Python programming. The course is structured into five modules, each focusing on a specific area of Python programming. You will start by learning about the basics of programming and setting up a Python development environment. From there, you will move on to topics such as data types, data structures, and control flow. Throughout the course, you will have access to interactive exercises and quizzes that will help you reinforce your learning. By the end of the course, you will have a solid understanding of Python programming and the ability to write your own simple programs. If you're new to programming or just starting out with Python, this course is the perfect place to begin. With clear, concise explanations and plenty of examples, you'll be up and running with Python in no time. Certification Upon completion of the course, learners can obtain a certificate as proof of their achievement. You can receive a £4.99 PDF Certificate sent via email, a £9.99 Printed Hardcopy Certificate for delivery in the UK, or a £19.99 Printed Hardcopy Certificate for international delivery. Each option depends on individual preferences and locations. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals who are new to programming Professionals who want to learn Python for data science or machine learning Students who want to gain a fundamental understanding of Python programming Anyone who wants to add a valuable skill to their resume Career path Python Developer: £30,000 - £75,000 per year Data Analyst: £24,000 - £46,000 per year Machine Learning Engineer: £35,000 - £85,000 per year Software Engineer: £24,000 - £70,000 per year Full Stack Developer: £28,000 - £70,000 per year Artificial Intelligence Developer: £35,000 - £85,000 per year
This course will show you how to create a professional and attractive user interface (UI) in Django for data science using the Semantic UI framework.
Python Programming: Beginner To Expert Overview Unfold the potential within you, and embark on a journey of mastering Python programming - from the fundamental building blocks to the pinnacle of expertise. This comprehensive course, crafted with meticulous care, empowers you to transform from a curious novice to a confident coding maestro, wielding Python's power with finesse. Within these engaging modules, you'll delve into the core principles of Python, meticulously exploring data types, operators, control flow, and functions. As your proficiency blossoms, you'll conquer advanced topics like object-oriented programming, powerful libraries like NumPy and Pandas, and the art of crafting polished scripts. But this journey isn't merely about acquiring technical prowess; it's about unlocking a world of possibilities. By the course's end, you'll be equipped to embark on a rewarding career path, armed with the skills to tackle real-world challenges in diverse domains - from data analysis and web development to scientific computing and automation. Learning Outcomes Gain a solid foundation in Python syntax, data structures, and control flow mechanisms. Master essential functions, user input, and error-handling techniques. Explore advanced data types, object-oriented programming concepts, and popular libraries like NumPy and Pandas. Craft polished, reusable Python scripts for various applications. Confidently navigate the Python ecosystem and continuously expand your knowledge. Why You Should Choose Python Programming: Beginner To Expert Lifetime access to the course No hidden fees or exam charges CPD Accredited certification on successful completion Full Tutor support on weekdays (Monday - Friday) Efficient exam system, assessment and instant results Download Printable PDF certificate immediately after completion Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. Improve your chance of gaining professional skills and better earning potential. Who is this Course for? Python Programming: Beginner To Expert is CPD certified and IAO accredited. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic backgrounds. Requirements Our Python Programming: Beginner To Expert is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Python Programming: Beginner To Expert Module 01: Introduction to Python Programming from A-Z Intro To Python Section Overview 00:06:00 What is Python Programming? 00:10:00 Who is This Course For? 00:05:00 Python Programming Marketplace 00:06:00 Python Job Opportunities 00:05:00 How To Land a Python Job Without a Degree 00:08:00 Python Programmer Job Roles 00:09:00 Python from A-Z Course Structure 00:04:00 Module 02: Getting Familiar with Python Getting Familiar with Python Section Overview 00:06:00 Installing Python on Windows 00:10:00 Anaconda and Jupyter Notebooks Part 1 00:08:00 Anaconda and Jupyter Notebooks Part 2 00:16:00 Comments 00:05:00 Python Syntax 00:02:00 Line Structure 00:03:00 Line Structure Exercise 00:07:00 Joining Lines 00:05:00 Multiple Statements on a Single Line 00:05:00 Indentation 00:08:00 Module 03: Basic Data Types Basic Data Types Section Overview 00:08:00 String Overview 00:10:00 String Manipulation 00:07:00 String Indexing 00:04:00 String Slicing 00:08:00 Printing 00:10:00 Python Variables 00:08:00 Integers and Floats 00:08:00 Booleans 00:02:00 Mini Project 1 : Letter Counter 00:20:00 Module 04: Python Operators Python Operators Section Overview 00:04:00 Comparison Operators 00:09:00 Arithmetic Operators 00:08:00 Assignment Operators 00:05:00 Logical Operators 00:13:00 Identity Operators 00:05:00 Membership Operators 00:02:00 Bitwise Operators 00:08:00 Module 05: Advanced Data Types Python Advanced Data Types Section Overview 00:11:00 Sets 00:06:00 List Overview 00:05:00 List Slicing and Indexing 00:04:00 Tuples 00:02:00 Dictionaries 00:11:00 When to use each one? 00:05:00 Compound Data Types 00:03:00 Module 06: Control Flow Part 1 Control Flow Part 1 Section Overview 00:15:00 Intro to Control Flow 00:01:00 Basic Conditional Statements 00:14:00 More Conditional Statements 00:05:00 For Loops 00:10:00 While Loops 00:12:00 Module 07: Control Flow Part 2 Control Flow Part 2 Section Overview 00:02:00 Break Statements 00:08:00 Continue Statements 00:05:00 Zip Function 00:07:00 Enumerate Function 00:04:00 List Comprehension 00:04:00 Module 08: Python Functions Python Functions Section Overview 00:03:00 Intro to Functions 00:02:00 Python help Function 00:03:00 Defining Functions 00:09:00 Variable Scope 00:08:00 Doc Strings 00:04:00 Module 09: User Input and Error Handling User Input and Error Handling Section Overview 00:02:00 Introduction to error handling 00:03:00 User Input 00:04:00 Syntax Errors 00:04:00 Exceptions 00:11:00 Handling Exceptions Part 1 00:08:00 Handling Exceptions Part 2 00:08:00 Module 10: Python Advanced Functions Python Advanced Functions Section Overview 00:05:00 Lambda Functions 00:05:00 Functions args and kwargs 00:10:00 Iterators 00:08:00 Generators and Yield 00:12:00 Map Function 00:14:00 Filter Function 00:08:00 Module 11: Python Scripting and Libraries Python Scripting and Libraries Section Overview 00:05:00 What is a script? 00:01:00 What is an IDE? 00:17:00 What is a text editor? 00:12:00 From Jupyter Notebook to VScode Part 1 00:15:00 From Jupyter Notebook to VScode Part 2 00:05:00 Importing Scripts 00:03:00 Standard Libraries 00:04:00 Third Party Libraries 00:06:00 Module 12: NumPy NumPy Section Overview 00:04:00 Why use NumPy? 00:04:00 NumPy Arrays 00:10:00 Reshaping, Accessing, and Modifying 00:07:00 Slicing and Copying 00:06:00 Inserting, Appending, and Deleting 00:10:00 Array Logical Indexing 00:04:00 Broadcasting 00:08:00 Module 13: Pandas Intro to Pandas 00:17:00 Pandas Series 00:17:00 Pandas Series Manipulation 00:17:00 Pandas DataFrame 00:17:00 Pandas DataFrame Manipulation 00:13:00 Dealing with Missing Values 00:10:00 Module 14: Introduction to OOP Functional vs OOP 00:06:00 OOP Key Definitions 00:04:00 Create your First Class 00:12:00 How to Create and Use Objects 00:06:00 How to Modify Attributes 00:12:00 Module 15: Advanced OOP Python Decorators 00:27:00 Property Decorator 00:09:00 Class Method Decorator 00:07:00 Static Methods 00:10:00 Inheritance from A to Z 00:21:00 Module 16: Starting a Career in Python Getting Started with Freelancing 00:09:00 Building A Brand 00:12:00 Personal Branding 00:13:00 Importance of Having Website/Blog 00:04:00 Do's and Don'ts of Networking 00:06:00 Creating A Python Developer Resume 00:06:00
Discover the power of data science and machine learning with Python! Learn essential techniques, algorithms, and tools to analyze data, build predictive models, and unlock insights. Dive into hands-on projects, from data manipulation to advanced machine learning applications. Elevate your skills and unleash the potential of Python for data-driven decision-making.
Overview This comprehensive course on Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Machine Learning with Python comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Machine Learning with Python is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 4 sections • 21 lectures • 01:34:00 total length •Introduction to types of ML algorithm: 00:02:00 •SVM - Python Implementation: 00:06:00 •Introduction to types of ML algorithm: 00:02:00 •Importing a dataset in python: 00:02:00 •Resolving Missing Values: 00:06:00 •Managing Category Variables: 00:04:00 •Training and Testing Datasets: 00:07:00 •Normalizing Variables: 00:02:00 •Normalizing Variables - Python Code: 00:03:00 •Summary: 00:01:00 •Simple Linear Regression - How it works?: 00:04:00 •Simple Linear Regreesion - Python Implementation: 00:07:00 •Multiple Linear Regression - How it works?: 00:01:00 •Multiple Linear Regression - Python Implementation: 00:09:00 •Decision Trees - How it works?: 00:05:00 •Random Forest - How it works?: 00:03:00 •Decision Trees and Random Forest - Python Implementation: 00:04:00 •kNN - How it works?: 00:02:00 •kNN - Python Implementation: 00:10:00 •Decision Tree Classifier and Random Forest Classifier in Python: 00:10:00 •SVM - How it works?: 00:04:00
Register on the Coding with Python 3 today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion. The Coding with Python 3 is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Coding with Python 3 Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Coding with Python 3, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content Module 01: Introduction and Setup Introduction 00:03:00 Why is Python 3 worth learning 00:04:00 Installing Python 3 on Windows 00:08:00 Installing Python 3 on Ubuntu and Mac 00:08:00 Taking a closer look at Python 3 IDLE 00:05:00 Module 02: Python Programming Basics Math operators 00:12:00 Strings 00:08:00 Variables and variable naming rules 00:11:00 Our first program 00:12:00 Type, len, str, int, float, functions 00:09:00 True or false Boolean 00:10:00 If-statement 00:05:00 If and else 00:13:00 Using elif for multiple statements.mp4 00:09:00 While loop 00:16:00 Infinite loops with break 00:07:00 Using continue in a loop.mp4 00:06:00 For Loop 00:10:00 Importing Python libraries 00:12:00 Module 03: Functions- Coding Exercises Defining functions in Python 3 00:15:00 Local and global variables 00:10:00 Coding guess the number program 00:16:00 Reverse a string function 00:07:00 Calculate area of a circle program 00:11:00 Simple Python calculator 00:15:00 Removing vowels from string program 00:13:00 Find the largest number out of three 00:16:00 Module 04: Lists, Tuples and Dictionaries Python lists 00:15:00 Creating smaller lists out of a bigger one 00:09:00 Manipulating lists and elements 00:08:00 Append, insert, remove, sort 00:11:00 Tuples 00:13:00 Introduction to dictionaries 00:10:00 Values, keys, items, get 00:08:00 Dictionary comprehension part 1 00:08:00 Dictionary comprehension part 2.mp4 00:07:00 Advanced string manipulation 00:12:00 Upper, lower, isupper, islower 00:09:00 Split, strip, join, startswith, endswith 00:13:00 Module 05: Files in Python 3 Navigating through system with OS library 00:29:00 Reading and writing to files 00:16:00 Reversing text from a file 00:17:00 Module 06: Error Handling Try and except 00:13:00 Try and finally 00:15:00 Module 07: Object Oriented Programming Classes 00:22:00 Changing class attributes 00:10:00 Built in class attributes 00:08:00 Using your class in a different program 00:05:00 Using your class in a program 00:26:00 Implementing students count option 00:05:00 Class inheritance 00:12:00 Overriding methods in a class 00:08:00 Module 08: Date & Time Printing and calculating date and time 00:30:00 Different date formats 00:09:00 Module 09: Regular Expressions Extracting useful data 00:23:00 Regex part 1 00:23:00 Regex part 2 00:17:00 Module 10: Interacting with HTTP Performing HTTP GET requests 00:20:00 Performing POST requests 00:04:00 Handling website redirections 00:03:00 BeautifulSoup 00:29:00 Encoding in requests 00:11:00 Session objects and cookies 00:21:00 SSL certificate, authentication, etc 00:21:00 JSON library and proxies 00:21:00 Module 11: Networking in Python 3 Socket terminology 00:09:00 Connecting two machines 00:21:00 Coding a chat program 00:35:00 Receiving desired amount of data 00:20:00 Socket timeout and options 00:08:00 UDP server and client 00:13:00 AF_UNIX and raw_sockets 00:14:00 Module 12: Threading Introduction to threading part 1 00:28:00 Introduction to the threading part 2 00:22:00 Theory behind threaded server 00:15:00 Module 13: E-mails, PDFs, Images Sending emails using smtplib 00:32:00 PDF files 00:11:00 Images in Python 3 00:16:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.
In this course, you will learn the fundamentals of data visualization in Python using the well-known Matplotlib and Seaborn data science libraries and perform exploratory data analysis (EDA) by visualizing a data set using a variety of charts.