Learning Outcomes After completing this course, learners will be able to: Learn Python for data analysis using NumPy and Pandas Acquire a clear understanding of data visualisation using Matplotlib, Seaborn and Pandas Deepen your knowledge of Python for interactive and geographical potting using Plotly and Cufflinks Understand Python for data science and machine learning Get acquainted with Recommender Systems with Python Enhance your understanding of Python for Natural Language Processing (NLP) Description Whether you are from an engineering background or not you still can efficiently work in the field of data science and the machine learning sector, if you have proficient knowledge of Python. Since Python is the easiest and most used programming language, you can start learning this language now to advance your career with the Data Science And Machine Learning Using Python : A Bootcamp course. This course will give you a thorough understanding of the Python programming language. Moreover, it will show how can you use Python for data analysis and machine learning. Alongside that, from this course, you will get to learn data visualisation, and interactive and geographical plotting by using Python. The course will also provide detailed information on Python for data analysis, Natural Language Processing (NLP) and much more. Upon successful completion of this course, get a CPD- certificate of achievement which will enhance your resume and career. Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post. Method of Assessment After completing this course, you will be provided with some assessment questions. To pass that assessment, you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly. Career Path After completing this course, you can explore various career options such as Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst In the UK professionals usually get a salary of £25,000 - £30,000 per annum for these positions. Course Content Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Machine Learning using Python : A Bootcamp 00:00:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 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.
Overview of Learn Linux in 5 Days Join our Learn Linux in 5 Days course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Learn Linux in 5 Days course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Learn Linux in 5 Days course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Learn Linux in 5 Days Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Learn Linux in 5 Days. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online — Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion – Digital / PDF Certificate After completing the Learn Linux in 5 Days course, you can order your CPD Accredited Digital/ PDF Certificate for £5.99. Certificate of Completion – Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Learn Linux in 5 Days is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. This course has been developed with maximum flexibility and accessibility, making it ideal for people who don’t have the time to devote to traditional education. Requirements You don’t need any educational qualification or experience to enrol in the Learn Linux in 5 Days course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Learn Linux in 5 Days Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Unit 01: Overview Course Overview 00:03:00 Unit 02: Day 1 Background and Introduction 00:07:00 Linux Distributions 00:05:00 Installing VirtualBox on Windows 00:03:00 Installing VirtualBox on Mac 00:03:00 Installing Linux Using an Image for VirtualBox 00:05:00 VirtualBox Troubleshooting Tips 00:02:00 When to Install Linux from Scratch 00:15:00 Installing CentOS from Scratch / CentOS Manual Installation Process 00:23:00 Getting Connected 00:11:00 Connect Directly 00:02:00 Unit 03: Day 2 The Linux Directory Structure 00:10:00 The Shell 00:08:00 Basic Linux Commands 00:05:00 Teach Yourself to Fish 00:06:00 Working with Directories 00:09:00 Listing Files and Understanding LS Output 00:12:00 Unit 04: Day 3 File and Directory Permissions Explained - Part One 00:11:00 File and Directory Permissions Explained - Part Two 00:09:00 View Files and the Nano Editor 00:05:00 Editing Files in Vi 00:10:00 Editing Files with Emacs 00:06:00 Finding Files and Directories 00:07:00 Graphical Editors 00:04:00 Unit 05: Day 4 Deleting, Copying, Moving, and Renaming Files 00:11:00 Wildcards - Part One 00:05:00 Wildcards - Part Two 00:07:00 Input, Output, and Redirection 00:08:00 Comparing Files 00:04:00 Searching in Files and Using Pipes 00:10:00 Transferring and Copying Files over the Network 00:07:00 Customizing the Shell Prompt 00:05:00 Shell Aliases 00:04:00 Unit 06: Day 5 Environment Variables 00:08:00 Processes and Job Control 00:12:00 Scheduling Repeated Jobs with Cron 00:06:00 Switching Users and Running Commands as Others 00:08:00 Shell History and Tab Completion 00:13:00 Installing Software on RPM Based Linux Distros: RedHat, CentOS, AlmaLinux, Rocky 00:21:00 Installing Software on Debian Based Linux Distros: Debian, Ubuntu, Kali Linux 00:12:00 Conclusion - Congratulations and Thank You! 00:01:00 Unit 07: Addendum - Connecting to a Linux Virtual Machine over the Network Connecting to a Linux Virtual Machine over the Network 00:11:00 Unit 08: Bonus Bonus - Installing NGINX, MySQL, PHP, and WordPress on Ubuntu 00:09:00 Unit 09: Resources Resources 00:15:00
About Course Learn how to use Linux to boost your programming productivity and become a more efficient developer. In this comprehensive course, you will learn: The best Linux terminals to use for programming How to use clipboard managers to save time and effort How to use Vim, the most powerful text editor for programmers How to use Zsh and the oh-my-zsh framework to customize your terminal experience Extensive lessons on terminal commands, including how to find and replace text, work with pipes and subshells, and automate tasks And much more! You will also receive access to a repository of scripts and an eBook containing all of the examples and explanations from the course. This course is perfect for programmers who are new to Linux or who want to learn how to use Linux more effectively. Enroll today and start your journey to becoming a more productive programmer with Linux! Here are some of the benefits of learning how to use Linux for programming: Linux is a powerful and flexible operating system that can be customized to meet your specific needs. Linux is also very efficient, which can make a big difference in your productivity, especially when working with large projects. Linux has a wide range of built-in tools and utilities that are designed for programmers, such as the Bash shell, Vim, and Git. Linux is also open source, which means that there is a large community of developers who are constantly contributing to and improving the platform. If you are serious about becoming a more productive programmer, then learning how to use Linux is an essential skill. This course will teach you everything you need to know to get started. Enroll today and start boosting your productivity! What Will You Learn? I'll increase my terminal productivity by using Terminator, Guake and other tools I'll be able to use regular expressions, pipes and subshells and external shell scripting libraries I'll work with files like a vim-fu master I'll increase my command line productivity (by learning how to use sed, find, tmux, network, autoenv and more) I'll be able to launch a webserver, modify images and productively work with Git I'll edit files without leaving the terminal, use the screen space efficiently and copy-paste like a pro All in all: I will double my terminal productivity Course Content Introduction Introduction Terminator- Hasta La Vista Terminal Guake - Not Quake! Clipit- Forget Everything, Paste from History Productive Shells: Reinvent The Way You Work Pre Chapter Vim Oh-my-zsh Your Terminal Never Felt This Good Before! Basic Regular Expressions Pipes and Subshells Your Shell's Salt and Pepper Shell Scripting for Fun and Profit Shell Scripting Libraries Vim Kung Fu Supercharging Vim Keyboard Kung Fu Plugin Steroids for Vim Vim Password Manager Extra- Fast Configuration Restore CLI: The Hidden Recipe Sed - One-Liner Productivity Treasure You Can Run, But You Can't Hide From 'Find' Tmux Virtual Consoles, Background Jobs and The Likes Network Who's Listening Autoenv Set a Lasting, Project-Based Habitat Don't rm The Trash Developers' Treasure On the Spot Webserver Shrinking Spells and Other Image Magic Go With the Git Flow Merge Git Conflicts With Ease From Localhost to Instant DNS JSON Jamming in The New Age No More Mister Nice Guy Closing Chapter Bonus Chapter Terminal Art Bonus Chapter Closing Chapter A course by Bogdan Vaida Experiential Trainer RequirementsYou need to have prior experience in the Linux command lineYou must have access to a Linux/Unix terminalBasic programming skills are recommended (but not required)Some basic shell scripting and web development knowledge make the course easier to understand Audience System administrators Developers who already know the basics of Linux and want to sharpen their skills People working in the Linux command line This course is not for people who are opening a terminal for the first time Audience System administrators Developers who already know the basics of Linux and want to sharpen their skills People working in the Linux command line This course is not for people who are opening a terminal for the first time
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