239 Data Structures & Algorithms (DSA) courses

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

Get up to speed with automating repetitive tasks with Python

Unlock the door to endless possibilities with our comprehensive bundle of courses: "Python for Machine Learning and Data Analytics." In the UK, professionals in these fields can enjoy lucrative career opportunities with average annual salaries ranging from £40,000 to £80,000+. Imagine yourself at the forefront of technological advancements, harnessing the power of Python programming to revolutionise data analysis, develop intelligent systems, and make informed business decisions. Introducing our captivating bundle of courses: "Python for Machine Learning and Data Analytics." Whether you're a novice seeking to enter the world of Python programming or an experienced professional looking to enhance your skills, this bundle is tailor-made for you. Each course in this bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This bundle promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development. Immerse yourself in these diverse, enthralling subjects, each designed to fuel your curiosity and enhance your knowledge. Dive in now! The courses in this bundle include: Python For Beginners Machine Learning Basics Data Analytics Learning outcomes: Gain proficiency in Python programming, from the basics to more advanced concepts, allowing you to develop efficient and robust code for data analysis and machine learning applications. Understand the fundamental principles of machine learning, including different algorithms and techniques, enabling you to train models, make predictions, and evaluate their performance. Acquire practical knowledge in data preprocessing, exploration, and visualisation techniques, empowering you to extract meaningful insights from complex datasets. Develop the skills to implement machine learning algorithms and techniques in Python, creating intelligent systems that can adapt and learn from data. Learn to effectively use Python libraries and frameworks such as NumPy, Pandas and Scikit-learn to streamline your data analysis and machine learning workflows. Gain hands-on experience by working on real-world projects and exercises, solidifying your understanding of Python programming, machine learning, and data analytics. Introducing our captivating bundle of courses: "Python for Machine Learning and Data Analytics." Whether you're a novice seeking to enter the world of Python programming or an experienced professional looking to enhance your skills, this bundle is tailor-made for you. The Python For Beginners course comprehensively introduces Python programming. You will learn the basics of Python syntax, data structures, control flow, and functions. By the end of this course, you will have a solid understanding of Python fundamentals and be ready to dive deeper into advanced concepts. In the Machine Learning Basics course, you will explore the fundamentals of machine learning. You will learn different machine learning algorithms, such as regression, classification, and clustering, and understand how to train and evaluate models. Through hands-on projects, you will gain practical experience in developing machine-learning solutions. The Data Analytics course focuses on the art of extracting insights from data. You will learn data preprocessing techniques, exploratory data analysis, and data visualisation using Python libraries such as NumPy, Pandas, and Matplotlib. This course will equip you with the skills to make data-driven decisions and effectively communicate findings. CPD 25 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This course is ideal for the following: Aspiring data analysts seeking to enhance their skills in Python and data analytics. Professionals are interested in entering the field of machine learning and data science. Software developers want to expand their knowledge into machine learning and data analytics. Business analysts who want to leverage Python and data analytics to gain valuable insights. Students or graduates looking to enhance their employability with in-demand skills. Career path People tend to pursue these career paths in this sector: Data Analyst: £25,000 - £45,000 per year Machine Learning Engineer: £40,000 - £70,000 per year Data Scientist: £45,000 - £80,000 per year Business Analyst: £30,000 - £55,000 per year Python Developer: £35,000 - £60,000 per year Data Engineer: £40,000 - £70,000 per year Research Scientist: £40,000 - £75,000 per year Certificates Certificate Of Completion Digital certificate - Included Certificate Of Completion Hard copy certificate - £9.99 Unlock your potential and showcase your accomplishments with our CPD Quality Standards certificates! Upon successful completion of the course, learners can obtain a CPD Quality Standards PDF certificate for Python For Beginners Part 1 absolutely free! Upon finishing Machine Learning Basics and Data Analytics, you'll have the opportunity to obtain valuable proof of your achievement. For just £4.99, we'll send you a CPD Quality Standards PDF Certificate via email, or if you prefer, you can get a beautifully printed hardcopy certificate for £9.99 in the UK. If you're located internationally, don't worry! We offer a printed hardcopy certificate for £14.99, ensuring your success knows no boundaries. Grab your certificate and celebrate your success today!

Using Ansible to automate local and cloud configuration management tasks with Playbooks

Overview This comprehensive course on SQL NoSQL Big Data and Hadoop will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This SQL NoSQL Big Data and Hadoop comes with accredited certification from CPD, 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? At the end of the course there will be an online written test, which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this SQL NoSQL Big Data and Hadoop. It is available to all students, of all academic backgrounds. Requirements Our SQL NoSQL Big Data and Hadoop 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 Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 14 sections • 130 lectures • 22:34:00 total length •Introduction: 00:07:00 •Building a Data-driven Organization - Introduction: 00:04:00 •Data Engineering: 00:06:00 •Learning Environment & Course Material: 00:04:00 •Movielens Dataset: 00:03:00 •Introduction to Relational Databases: 00:09:00 •SQL: 00:05:00 •Movielens Relational Model: 00:15:00 •Movielens Relational Model: Normalization vs Denormalization: 00:16:00 •MySQL: 00:05:00 •Movielens in MySQL: Database import: 00:06:00 •OLTP in RDBMS: CRUD Applications: 00:17:00 •Indexes: 00:16:00 •Data Warehousing: 00:15:00 •Analytical Processing: 00:17:00 •Transaction Logs: 00:06:00 •Relational Databases - Wrap Up: 00:03:00 •Distributed Databases: 00:07:00 •CAP Theorem: 00:10:00 •BASE: 00:07:00 •Other Classifications: 00:07:00 •Introduction to KV Stores: 00:02:00 •Redis: 00:04:00 •Install Redis: 00:07:00 •Time Complexity of Algorithm: 00:05:00 •Data Structures in Redis : Key & String: 00:20:00 •Data Structures in Redis II : Hash & List: 00:18:00 •Data structures in Redis III : Set & Sorted Set: 00:21:00 •Data structures in Redis IV : Geo & HyperLogLog: 00:11:00 •Data structures in Redis V : Pubsub & Transaction: 00:08:00 •Modelling Movielens in Redis: 00:11:00 •Redis Example in Application: 00:29:00 •KV Stores: Wrap Up: 00:02:00 •Introduction to Document-Oriented Databases: 00:05:00 •MongoDB: 00:04:00 •MongoDB Installation: 00:02:00 •Movielens in MongoDB: 00:13:00 •Movielens in MongoDB: Normalization vs Denormalization: 00:11:00 •Movielens in MongoDB: Implementation: 00:10:00 •CRUD Operations in MongoDB: 00:13:00 •Indexes: 00:16:00 •MongoDB Aggregation Query - MapReduce function: 00:09:00 •MongoDB Aggregation Query - Aggregation Framework: 00:16:00 •Demo: MySQL vs MongoDB. Modeling with Spark: 00:02:00 •Document Stores: Wrap Up: 00:03:00 •Introduction to Search Engine Stores: 00:05:00 •Elasticsearch: 00:09:00 •Basic Terms Concepts and Description: 00:13:00 •Movielens in Elastisearch: 00:12:00 •CRUD in Elasticsearch: 00:15:00 •Search Queries in Elasticsearch: 00:23:00 •Aggregation Queries in Elasticsearch: 00:23:00 •The Elastic Stack (ELK): 00:12:00 •Use case: UFO Sighting in ElasticSearch: 00:29:00 •Search Engines: Wrap Up: 00:04:00 •Introduction to Columnar databases: 00:06:00 •HBase: 00:07:00 •HBase Architecture: 00:09:00 •HBase Installation: 00:09:00 •Apache Zookeeper: 00:06:00 •Movielens Data in HBase: 00:17:00 •Performing CRUD in HBase: 00:24:00 •SQL on HBase - Apache Phoenix: 00:14:00 •SQL on HBase - Apache Phoenix - Movielens: 00:10:00 •Demo : GeoLife GPS Trajectories: 00:02:00 •Wide Column Store: Wrap Up: 00:05:00 •Introduction to Time Series: 00:09:00 •InfluxDB: 00:03:00 •InfluxDB Installation: 00:07:00 •InfluxDB Data Model: 00:07:00 •Data manipulation in InfluxDB: 00:17:00 •TICK Stack I: 00:12:00 •TICK Stack II: 00:23:00 •Time Series Databases: Wrap Up: 00:04:00 •Introduction to Graph Databases: 00:05:00 •Modelling in Graph: 00:14:00 •Modelling Movielens as a Graph: 00:10:00 •Neo4J: 00:04:00 •Neo4J installation: 00:08:00 •Cypher: 00:12:00 •Cypher II: 00:19:00 •Movielens in Neo4J: Data Import: 00:17:00 •Movielens in Neo4J: Spring Application: 00:12:00 •Data Analysis in Graph Databases: 00:05:00 •Examples of Graph Algorithms in Neo4J: 00:18:00 •Graph Databases: Wrap Up: 00:07:00 •Introduction to Big Data With Apache Hadoop: 00:06:00 •Big Data Storage in Hadoop (HDFS): 00:16:00 •Big Data Processing : YARN: 00:11:00 •Installation: 00:13:00 •Data Processing in Hadoop (MapReduce): 00:14:00 •Examples in MapReduce: 00:25:00 •Data Processing in Hadoop (Pig): 00:12:00 •Examples in Pig: 00:21:00 •Data Processing in Hadoop (Spark): 00:23:00 •Examples in Spark: 00:23:00 •Data Analytics with Apache Spark: 00:09:00 •Data Compression: 00:06:00 •Data serialization and storage formats: 00:20:00 •Hadoop: Wrap Up: 00:07:00 •Introduction Big Data SQL Engines: 00:03:00 •Apache Hive: 00:10:00 •Apache Hive : Demonstration: 00:20:00 •MPP SQL-on-Hadoop: Introduction: 00:03:00 •Impala: 00:06:00 •Impala : Demonstration: 00:18:00 •PrestoDB: 00:13:00 •PrestoDB : Demonstration: 00:14:00 •SQL-on-Hadoop: Wrap Up: 00:02:00 •Data Architectures: 00:05:00 •Introduction to Distributed Commit Logs: 00:07:00 •Apache Kafka: 00:03:00 •Confluent Platform Installation: 00:10:00 •Data Modeling in Kafka I: 00:13:00 •Data Modeling in Kafka II: 00:15:00 •Data Generation for Testing: 00:09:00 •Use case: Toll fee Collection: 00:04:00 •Stream processing: 00:11:00 •Stream Processing II with Stream + Connect APIs: 00:19:00 •Example: Kafka Streams: 00:15:00 •KSQL : Streaming Processing in SQL: 00:04:00 •KSQL: Example: 00:14:00 •Demonstration: NYC Taxi and Fares: 00:01:00 •Streaming: Wrap Up: 00:02:00 •Database Polyglot: 00:04:00 •Extending your knowledge: 00:08:00 •Data Visualization: 00:11:00 •Building a Data-driven Organization - Conclusion: 00:07:00 •Conclusion: 00:03:00 •Assignment -SQL NoSQL Big Data and Hadoop: 00:00:00

Coding (Computer Programming) Master the knowledge and skills needed to become a good programmer Coding is a cornerstone of the digital age, influencing everything from the technology we use daily to the applications we rely on. Mastering various aspects of coding and computer programming is essential for anyone looking to excel in this field. The Coding (Computer Programming) Diploma provides comprehensive training on crucial programming concepts, including binary systems, algorithm analysis, and data storage. Additionally, you will gain practical skills in arrays, linked lists, stacks, and queues. This diploma course is designed to equip you with the necessary knowledge and technical skills to become proficient in coding. Through detailed modules and hands-on practice, you’ll learn how to tackle complex problems, write efficient code, and understand fundamental computer science principles. This in-depth training ensures you are well-prepared to enter the programming industry with confidence. Embrace the opportunity to advance your coding skills and enhance your career prospects. By enrolling in the Coding (Computer Programming) Diploma, you'll position yourself for success in a competitive job market. Start your journey today and gain the expertise needed to excel as a skilled programmer. This Coding (Computer Programming) Bundle Consists of the following Premium courses: Course 01: Coding with HTML, CSS, & JavaScript Course 02: Computer Science With Python Course 03: Python Programming for Everybody Course 04: Ultimate PHP & MySQL Web Development Course & OOP Coding Course 05: Ethical Hacking Course 06: Complete Web Application Penetration Testing & Security Course 07: Diploma in PHP Web Development Course 08: Front End Web Development Diploma Course 09: SQL Server for Beginners Course 10: Cloud Computing / CompTIA Cloud+ (CV0-002) Course 11: Level 3 Cyber Security Key Features of the Course: FREE Coding (Computer Programming) Diploma CPD-accredited certificate Get a free student ID card with Coding (Computer Programming) Diploma training (£10 applicable for international delivery) Lifetime access to the Coding (Computer Programming) Diploma course materials The Coding (Computer Programming) Diploma program comes with 24/7 tutor support Get instant access to this Coding (Computer Programming) Diploma course Learn Coding (Computer Programming) Diploma training from anywhere in the world The Coding (Computer Programming) Diploma training is affordable and simple to understand The Coding (Computer Programming) Diploma training is entirely online Learning Outcomes of Coding (Computer Programming): Gain the knowledge, skills and guidelines of coding (computer programming) Ability to do coding with HTML, CSS, Javascript & Python Learn how to create your first responsive website Get a comprehensive understanding of ethical hacking and web hacking Explore complete web application penetration testing & security Gain expertise in PHP web development & Front End web development Discover SQL Server and how it is used to manage and store information Become fully aware of Cloud Computing and why it is needed Description The Coding (Computer Programming) Diploma provides an in-depth exploration of essential programming concepts and practices. This comprehensive course covers everything from binary systems and algorithm analysis to data structures such as arrays, linked lists, stacks, and queues. With practical hands-on training, you'll develop the skills needed to tackle complex coding challenges and build efficient, effective programs. Perfect for those seeking to enhance their technical expertise or launch a career in programming, this diploma offers the foundational knowledge and practical experience required to succeed in the dynamic field of computer science. Curriculum of Coding (Computer Programming) Bundle Course 01: Coding with HTML, CSS, & JavaScript Welcome HTML 5 CSS 3 Bootstrap Project 1 - Design a Landing Page Project 2 - Business Website Project 3 - Portfolio ~~~~~Other Courses are included in this Coding (Computer Programming Training) Bundle~~~~~ Course 02: Computer Science With Python Course 03: Python Programming for Everybody Course 04: Create Your First Responsive Website Course 05: Ethical Hacking Course 06: Complete Web Application Penetration Testing & Security Course 07: Diploma in PHP Web Development Course 08: Front End Web Development Diploma Course 09: SQL Server for Beginners Course 10: Cloud Computing / CompTIA Cloud+ (CV0-002) Course 11: Level 3 Cyber Security How will I get my Coding (Computer Programming) Certificate? After successfully completing the Coding (Computer Programming) bundle, you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (Previously, it was £6*11 = £66) Hard Copy Certificate: Free ((Previously, it was £10) CPD 130 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Our Coding (Computer Programming) Diploma course is for anyone looking to upskill their career in any IT field. Requirements Our Coding (Computer Programming) is fully compatible with PC's, Mac's, laptops, tablets and Smartphone devices. Career path Explore diverse career opportunities with our Coding with Scratch course: Junior Software Developer: £25,000 - £35,000 Game Designer: £28,000 - £40,000 Coding Instructor: £22,000 - £30,000 Interactive Media Designer: £30,000 - £45,000 Educational Technologist: £25,000 - £38,000 App Developer: £30,000 - £50,000 Certificates Certificate of completion Digital certificate - Included You will get the Hard Copy certificate for the title course (Coding with HTML, CSS, & JavaScript) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost. Certificate of completion Digital certificate - Included

Description: In developing a website, it is important to choose a subject or theme that will suit your style and preference. In this course, you will learn to decide on the function and niche of your site. You will learn the importance of visualization and how to make your site content-rich. You will also be able to know how to do back links. Then you will see the significance of SEO, multimedia, and social sites to improve the traffic of your website. Who is the course for? Employees of the business industry and other businessmen who want to learn how to become profitable through website designing. People who have an interest in Website Design and Marketing and how to effectively communicate with their potential clients through the web. Entry Requirement: This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Assessment:  At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. PDF certificate's turnaround time is 24 hours and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path: The Web Development Basics course will be very beneficial and helpful, especially to the following careers: Businessman Marketing and Promotions Specialists Marketing Managers Product Creators Programmers Sales Managers Sales and Promotions Specialists Top Executives Website Developer. Updated Version - Web Development Basics Section 01: Getting Started Introduction 00:03:00 How to Get Course requirements 00:02:00 Getting Started on Windows, Linux or Mac 00:02:00 How to ask a Great Questions 00:01:00 FAQ's 00:01:00 Section 02: HTML Introduction HTML 00:05:00 Choosing Code Editor 00:06:00 Installing Code Editor (Sublime Text) 00:04:00 Overview of a Webpage 00:05:00 Structure of a Full HTML Webpage 00:07:00 First Hello World! Webpage 00:09:00 Section 03: HTML Basic Heading tags 00:09:00 Paragraph 00:08:00 Formatting Text 00:12:00 List Items Unordered 00:05:00 List Items Ordered 00:04:00 Classes 00:09:00 IDs 00:06:00 Comments 00:04:00 Section 04: HTML Intermediate Images 00:12:00 Forms 00:05:00 Marquee 00:06:00 Text area 00:06:00 Tables 00:06:00 Links 00:07:00 Navbar - Menu 00:04:00 HTML Entities 00:05:00 Div tag 00:06:00 Google Maps 00:07:00 Section 05: HTML Advanced HTML Audio 00:07:00 HTML Video 00:05:00 Canvas 00:06:00 Iframes 00:05:00 Input Types 00:04:00 Input Attributes 00:06:00 Registration Form 00:04:00 Contact Us Form 00:10:00 Coding Exercise 00:01:00 Solution for Coding Exercise 00:02:00 Section 06: JavaScript Introduction What is JavaScript 00:09:00 Hello World Program 00:14:00 Getting Output 00:11:00 Internal JavaScript 00:13:00 External JavaScript 00:09:00 Inline JavaScript 00:04:00 Async and defer 00:06:00 Section 07: JavaScript Basics Variables 00:13:00 Data Types 00:11:00 Numbers 00:06:00 Strings 00:06:00 String Formatting 00:05:00 Section 08: JavaScript Operators Arithmetic operators 00:07:00 Assignment operators 00:03:00 Comparison operators 00:06:00 Logical operators 00:08:00 Section 09: JavaScript Conditional Statements If-else statement 00:05:00 If-else-if statement 00:04:00 Section 10: JavaScript Control Flow Statements While loop 00:09:00 Do-while loop 00:03:00 For loop 00:08:00 Coding Exercise 00:02:00 Solution for Coding Exercise 00:02:00 Section 11: JavaScript Functions Creating a Function 00:07:00 Function Call() 00:07:00 Function with parameters 00:05:00 Section 12: JavaScript Error Handling Try-catch 00:05:00 Try-catch-finally 00:17:00 Section 13: JavaScript Client-Side Validations On Submit Validation 00:09:00 Input Numeric Validation 00:12:00 Section 14: Python Introduction Introduction to Python 00:02:00 Python vs Other Languages 00:04:00 Why It's Popular 00:04:00 Command Line Basics 00:07:00 Python Installation (Step By Step) 00:06:00 PyCharm IDE Installation 00:08:00 Getting Start PyCharm IDE 00:05:00 First Python Hello World Program 00:07:00 Section 15: Python Basic Variables 00:16:00 Data Types 00:13:00 Type Casting 00:07:00 User Inputs 00:08:00 Comments 00:04:00 Section 16: Python Strings Strings 00:05:00 String Indexing 00:05:00 String Slicing 00:04:00 String Built-in Functions 00:09:00 Formatting String (Dynamic Data) 00:05:00 Section 17: Python Operators Arithmetic Operators 00:08:00 Assignment Operators 00:05:00 Comparison Operators 00:05:00 Logical Operators 00:02:00 AND Operator 00:04:00 OR Operator 00:02:00 NOT Operator 00:03:00 Booleans 00:02:00 Section 18: Python Data Structures Arrays in Earler 00:02:00 Lists 00:06:00 Add List Items 00:07:00 Remove List Items 00:01:00 Sort Lists 00:03:00 Join Lists 00:08:00 Tuples 00:08:00 Update tuples 00:07:00 Join tuples 00:02:00 Dictionaries 00:06:00 Add Dictionary Items 00:04:00 Remove Dictionary Items 00:03:00 Nested Disctionaries 00:04:00 Sets 00:04:00 Add Set Items 00:03:00 Remove Set Items 00:01:00 Join Set Items 00:04:00 Section 19: Python Conditional Statements If Statement 00:03:00 If-else Statement 00:04:00 If-elif-else Statement 00:04:00 If Statement Coding Excercise 00:05:00 Section 20: Python Control Flow Statements Flow Charts 00:06:00 While Loops Statement 00:10:00 For Loops Statement 00:06:00 The range() Function 00:04:00 Nested Loops 00:04:00 2D List using Nested Loop 00:04:00 Section 21: Python Core Games Guessing Game 00:07:00 Car Game 00:10:00 Section 22: Python Functions Creating a Function 00:03:00 Calling a Function 00:06:00 Function with Arguments 00:05:00 Section 23: Python args, KW args for Data Science args, Arbitary Arguments 00:04:00 kwargs, Arbitary Keyword Arguments 00:06:00 Section 24: Python Project Project Overview 00:04:00 ATM RealTime Project 00:13:00 Old Version - Web Development Basics Web Development Basics What Are Niche Website? 01:00:00 The Role Of Visualization In Education 00:15:00 Identify Your Best Platform Or Software 01:00:00 Select A Web Host 01:00:00 Collect Your Site 00:15:00 Building A Content Rich Website 00:15:00 Build Backlinks 00:30:00 Use SEO, Multimedia And Social Sites 01:30:00 Use Analytics 01:00:00 Wrapping Up 00:15:00 Mock Exam Mock Exam-Web Development Basics 00:20:00 Final Exam Final Exam-Web Development Basics 00:20:00 Order Your Certificate and Transcript Order Your Certificates and Transcripts 00:00:00 Order Your Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

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Overview This comprehensive course on Python for Data Analysis will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Python for Data Analysis 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 Python for Data Analysis. It is available to all students, of all academic backgrounds. Requirements Our Python for Data Analysis 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 19 sections • 99 lectures • 00:08:00 total length •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 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 •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 •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 •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 •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 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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- Python for Data Analysis: 00:00:00