929 Courses delivered Online

The comprehensive Complete U&P AI - Natural Language Processing (NLP) with Python has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Complete U&P AI - Natural Language Processing (NLP) with Python today, and learn from the very best the industry has to offer! This best selling Complete U&P AI - Natural Language Processing (NLP) with Python has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Complete U&P AI - Natural Language Processing (NLP) with Python is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Complete U&P AI - Natural Language Processing (NLP) with Python is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The Complete U&P AI - Natural Language Processing (NLP) with Python is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the Complete U&P AI - Natural Language Processing (NLP) with Python, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Complete U&P AI - Natural Language Processing (NLP) with Python will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the Complete U&P AI - Natural Language Processing (NLP) with Python to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.  Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.

Unleash Your Coding Potential with the Ultimate Software Engineering Bundle! According to a recent study by Tech Nation, the UK's tech industry is booming, with an estimated 4.8 million tech workers contributing over £185 billion to the economy. It also shows a growing demand for skilled software engineers, with a projected job growth of 22% over the next decade and an average salary of £58,000 per year. Are you ready to embark on an incredible journey through the world of programming and software engineering? Our Software Engineering, Python, C++ , Javascript, CSS, HTML Coding bundle is meticulously curated to equip you with the essential skills and knowledge to thrive in this dynamic field. We've assembled a collection of 20 skill-boosting courses in this Software Engineering bundle that will teach you the fundamentals of programming, web development, machine learning, and more. You'll also gain valuable insights into cybersecurity, SaaS development, and game development, empowering you to pursue a diverse range of career paths. Don't miss out on this opportunity to enhance your coding prowess and ignite your software engineering journey. Enrol now and shape your future today! This Software Engineering, Python, C++ , Javascript, CSS, HTML Coding Bundle Contains 20 of Our Premium Courses for One Discounted Price: Course 01: Coding with Scratch Course 02: C# Programming - Beginner to Advanced Course 03: Machine Learning with Python Course Course 04: Basics of WordPress: Create Unlimited Websites Course 05: Modern PHP Web Development w/ MySQL, GitHub & Heroku Course 06: Node JS: API Development with Swagger Course 07: Refactor Javascript Course 08: Python Programming Bible | Networking, GUI, Email, XML, CGI Course 09: Web Application Penetration Testing Course Course 10: Penetration Testing with OWASP ZAP: Mastery course Course 11: How To Startup Your Own SaaS (Software As a Service) Company (SaaS Evolution) Course 12: Three.js & WebGL 3D Programming Crash Course Course 13: HTML Web Development Crash Course Course 14: CSS Web Development Crash Course Course 15: Flutter & Dart Development for Building iOS and Android Apps Course 16: Masterclass Bootstrap 5 Course - Responsive Web Design Course 17: Game Development using Cocos2d-x v3 C++ Course 18: C++ Development: The Complete Coding Guide Course 19: .NET Core API Development Course 20: Stripe with C# Learning Outcomes of Software Engineering Bundle: Fluent coding in Python, C++, JavaScript, and more. Web development mastery with HTML, CSS, and Bootstrap. Expertise in machine learning, AI, and 3D programming. Proficiency in WordPress, PHP, and Node.js. Penetration testing skills for enhanced cybersecurity. Creating iOS and Android apps using Flutter & Dart. Building a successful SaaS company from scratch. Why Choose Our Software Engineering Bundle? FREE Software Engineering certificate accredited Get a free student ID card with Software Engineering Training Get instant access to this Software Engineering course. Learn Software Engineering from anywhere in the world The Software Engineering is affordable and simple to understand The Software Engineering is an entirely online, interactive lesson with voiceover audio Lifetime access to the Software Engineering course materials The Software Engineering comes with 24/7 tutor support If you aim to enhance your Software Engineering skills, our comprehensive Software Engineering course is perfect for you. Designed for success, this Software Engineering course covers everything from basics to advanced topics in Software Engineering. Dive into the magic of coding with courses like "Coding with Scratch" and "C# Programming - Beginner to Advanced". Harness the power of AI and data with "Machine Learning with Python Course", and effortlessly create stunning websites with "Modern PHP Web Development w/ MySQL, GitHub & Heroku". Explore cutting-edge technologies such as "Node JS: API Development with Swagger" and "Three.js & WebGL 3D Programming Crash Course. With these courses, you'll not only master programming languages but also gain the skills to secure web applications with "Web Application Penetration Testing Course" and "Penetration Testing with OWASP ZAP: Mastery Course". Each lesson in this Software Engineering course is crafted for easy understanding, enabling you to become proficient in Software Engineering. Whether you are a beginner or looking to sharpen your existing skills, this Software Engineering is the ideal choice. CPD 200 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Software Engineering Bundle is ideal for: Aspiring programmers seeking comprehensive language expertise. Web developers aiming to build responsive and engaging sites. Tech enthusiasts interested in AI, machine learning, and 3D programming. Individuals looking to enter the world of app development. Requirements You will not need any prior background or expertise in this Software Engineering bundle. Career path This Software Engineering bundle will allow you to kickstart or take your career to the next stage in the related sector such as: Junior Software Engineer: £25,000 - £35,000 Web Developer: £30,000 - £40,000 Machine Learning Engineer: £40,000 - £55,000 App Developer: £35,000 - £45,000 Penetration Tester: £30,000 - £45,000 SaaS Entrepreneur: Potential for substantial earnings. Certificates Digital certificate Digital certificate - Included Hard copy certificate Hard copy certificate - Included

In this course, you will learn how to author machine learning models in Python without the aid of frameworks or libraries from scratch. Discover the process of loading data, evaluating models, and implementing machine learning algorithms.

Overview Mastering data science skills and expertise can open new doors of opportunities for you in a wide range of fields. Learn the fundamentals and develop a solid grasp of Python data science with the comprehensive Data Science with Python course. This course is designed to assist you in securing a valuable skill set and boosting your career. This course will provide you with quality training on the fundamentals of data analysis with Python. From the step-by-step learning process, you will learn the techniques of setting up the system. Then the course will teach you Python data structure and functions. You will receive detailed lessons on NumPy, Matplotlib, and Pandas. Furthermore, you will develop the skills for Algorithm Evaluation Techniques, visualising datasets and much more. After completing the course you will receive a certificate of achievement. This certificate will help you create an impressive resume. So join today! 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? This course Data Science with Python course is ideal for beginners in data science. It will help them develop a solid grasp of Python and help them pursue their dream career in the field of data science. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush. Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst And much more! Course Curriculum 90 sections • 90 lectures • 10:19:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:04:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:06:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

Build your own AI-driven image classifier web application

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.

Overview of Intermediate Python Coding Join our Intermediate Python Coding 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 Intermediate Python Coding course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Intermediate Python Coding 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! Get a Quick Look at The Course Content: This Intermediate Python Coding 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 Intermediate Python Coding. 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 Intermediate Python Coding 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 Intermediate Python Coding 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 Intermediate Python Coding 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 Intermediate Python Coding Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Frequently Asked Questions (FAQ's) Q. How do I purchase a course? 1. You need to find the right course on our IOMH website at first. You can search for any course or find the course from the Courses section of our website. 2. Click on Take This Course button, and you will be directed to the Cart page. 3. You can update the course quantity and also remove any unwanted items in the CART and after that click on the Checkout option and enter your billing details. 4. Once the payment is made, you will receive an email with the login credentials, and you can start learning after logging into the portal. Q. I have purchased the course when will I be able to access the materials? After purchasing the course, you should receive an email with the login credentials within 24 hours. Please check your spam or junk folder if you didn't receive it in your inbox. You can access your courses by logging into your account. If you still need any assistance, please get in touch with our Customer Support team by providing the details of your purchase. Q. I haven't received my certificate yet. What should I do? You should receive your Digital Certificate within 24 hours after placing the order, and it will take 3-9 days to deliver the hard copies to your address if you are in the UK. For International Delivery, it will take 20-25 days. If you require any assistance, get in touch with our dedicated Customer Support team, and your queries/issues will be dealt with accordingly. Q. I don't have a credit/debit card, what other methods of payment do you accept? You can make the payment using PayPal or you can Bank Transfer the amount. For Bank transfer you will require an invoice from us and you need to contact our Customer Support team and provide details of your purchase to get the invoice. After that, you will receive an email with the invoice and bank details and you can make the payment accordingly. Q. Can I do the courses from outside UK? We are an online course provider, and learners from anywhere in the world can enrol on our courses using an internet-connected device. Q. When I log into the account it says 'Contact Administrator'. To resolve this issue, please log out of your account and then log back in. Course Curriculum Section 01: Introduction Course Introduction 00:02:00 Course Curriculum 00:05:00 How to get Pre-requisites 00:02:00 Getting Started on Windows, Linux or Mac 00:01:00 How to ask Great Questions 00:02:00 Section 02: Class Introduction to Class 00:07:00 Create a Class 00:09:00 Calling a Class Object 00:08:00 Class Parameters - Objects 00:05:00 Access Modifiers(theory) 00:10:00 Summary 00:02:00 Section 03: Methods Introduction to methods 00:06:00 Create a method 00:07:00 Method with parameters 00:12:00 Method default parameter 00:06:00 Multiple parameters 00:05:00 Method return keyword 00:04:00 Method Overloading 00:05:00 Summary 00:02:00 Section 04: OOPs Object-Oriented Programming Introduction to OOPs 00:05:00 Classes and Objects 00:08:00 Class Constructors 00:07:00 Assessment Test1 00:01:00 Solution for Assessment Test1 00:03:00 Summary 00:01:00 Section 05: Inheritance and Polymorphism Introduction 00:04:00 Inheritance 00:13:00 Getter and Setter Methods 00:12:00 Polymorphism 00:13:00 Assessment Test2 00:03:00 Solution for Assessment Test2 00:03:00 Summary 00:02:00 Section 06: Encapsulation and Abstraction Introduction 00:03:00 Access Modifiers (public, protected, private) 00:21:00 Encapsulation 00:07:00 Abstraction 00:07:00 Summary 00:02:00 Section 07: Python Games for Intermediate Introduction 00:01:00 Dice Game 00:06:00 Card and Deck Game Playing 00:07:00 Summary 00:01:00 Section 08: Modules and Packages Introduction 00:01:00 PIP command installations 00:12:00 Modules 00:12:00 Naming Module 00:03:00 Built-in Modules 00:03:00 Packages 00:08:00 List Packages 00:03:00 Summary 00:02:00 Section 09: Working Files with Pandas Introduction 00:02:00 Reading CSV files 00:11:00 Writing CSV files 00:04:00 Summary 00:01:00 Section 10: Error and ExceptionHandling Introduction 00:01:00 Errors - Types of Errors 00:08:00 Try - Except Exceptions Handling 00:07:00 Creating User-Defined Message 00:05:00 Try-Except-FinallyBlocks 00:07:00 Summary 00:02:00

Duration 3 Days 18 CPD hours This course is intended for This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their Python proficiencies. Overview In this course, students will expand their Python proficiencies. Students will: Create object-oriented Python applications. Design and create a GUI. Store data in a database from Python applications. Communicate using client/server network protocols. Manage multiple processes with threading. Implement unit testing. Package an application for distribution. Students will build upon basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, threading, unit testing, and creating and installing packages. Usinig Object-Oriented Python Create and Use Classes in an Application Use Magic Methods Incorporate Class Factories Creating a GUI Design a GUI Create and Arrange a GUI Layout Interact with User Events Using Databases Basics of Data Management Use SQLite Databases Manipulate SQL Data Network Programming Basics of Network Programming Create a Client/Server Program Managing Multiple Processes with Threading Create a Threaded Application Manage Thread Resources Implementing Unit Testing Test-Driven Development Write and Run a Unit Test Case Create a Test Suite Packaging an Application for Distribution Create a Package Structure Generate the Package Distribution Files Generate a Windows Executable Additional course details: Nexus Humans Python Programming - Advanced training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Python Programming - Advanced course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

About Course Data Science and Data Analytics with Python: A Comprehensive Course for Beginners Unlock the power of data and gain insights that drive informed decisions with this comprehensive course on data science and data analytics with Python. This course is designed for beginners of all skill levels, with no prior programming experience required. You will learn the essential skills to embark on your data-driven journey, including: Data manipulation with NumPy and Pandas Data visualization with Matplotlib and Seaborn Statistical analysis with Python Machine learning and artificial intelligence You will also gain hands-on experience with real-world data projects, allowing you to apply your newfound knowledge to solve real-world problems. By the end of this course, you will be able to: Understand the fundamentals of data science and data analytics Apply Python to manipulate, visualize, and analyze data Use Python to build machine learning and artificial intelligence models Solve real-world data problems This course is the perfect launchpad for your data science journey. Whether you are looking to pivot your career, enhance your skill set, or simply quench your curiosity, this course will give you the foundation you need to succeed. Enroll today and start exploring the fascinating world of data science together! What Will You Learn? Understand the fundamentals of data science and data analytics Apply Python to manipulate, visualize, and analyze data Use Python to build machine learning and artificial intelligence models Solve real-world data problems Course Content Introduction to Python Data Science Introduction to Python Data Science Environment Setup Data Cleaning Packages Working with the Numpy package Working with Pandas Data science package Data Visualization Packages Working with Matplotlib Data Science package (Part - 1) Working with Matplotlib Data Science (Part - 2) A course by Uditha Bandara Microsoft Most Valuable Professional (MVP) RequirementsBeginners level knowledge for working with Data .Programming knowledge not required. Audience Beginners with no prior programming experience Anyone interested in learning data science and data analytics Audience Beginners with no prior programming experience Anyone interested in learning data science and data analytics

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step