466 Courses in Cardiff delivered On Demand

Getting Started The main aim of the OTHM Level 7 Diploma in Data Science is to enhance the knowledge and skills required to extract business-oriented insights from data. This involves comprehending how value and information circulate in a business and utilising this knowledge to recognise potential business prospects.The main aim of the OTHM Level 7 Diploma in Data Science is to enhance the knowledge and skills required to extract business-oriented insights from data. This involves comprehending how value and information circulate in a business and utilising this knowledge to recognise potential business prospects. Key Benefits This qualification will bring you many vital benefits, such as; Learners can gain the essential subject knowledge needed to progress successfully into further study or the world of work. Refreshed content that is closely aligned with employer and higher education needs Develop a comprehensive knowledge of classical data analytics, including statistical inference, predictive modelling, time series analysis and data reduction. Become familiar with and use the tools and techniques used in data visualisation. Assessments that consider cognitive skills along with affective and applied skills Key Highlights Do you wish to be a Data Scientist? Then, The OTHM Level 7 Diploma in Data Science program offered by the School of Business and Technology London is the right solution for you. Remember! The assessment for the qualification is done based on assignments only, and you do not need to worry about writing any exam. With the School of Business and Technology London, you can complete the qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our OTHM-approved tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways The OTHM Level 7 Diploma in Data Science can open many career pathways including, but not limited to: Data scientist- Est. Salary £59,680 Data Analyst- Est. Salary £42,984 Business Analyst-Est. Salary £54,413   About Awarding Body OTHM is an established and recognised Awarding Organisation (Certification Body) launched in 2003. OTHM has already made a mark in the UK and global online education scenario by creating and maintaining a user-friendly and skill based learning environment. OTHM has both local and international recognition which aids OTHM graduates to enhance their employability skills as well as allowing them to join degree and/or Master top-up programmes. OTHM qualifications has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Business Studies, Leadership, Tourism and Hospitality Management, Health and Social Care, Information Technology, Accounting and Finance, Logistics and Supply Chain Management. Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. UNIT1- Data Science Foundations Reference No : Unit 1 - F/650/5562 Credit : 20 || TQT : 200 Hours This unit introduces various data science concepts, including data administration, governance, and big data sources. UNIT2- Probability and Statistics for Data Analysis Reference No : Unit 2 - H/650/5563 Credit : 20 || TQT : 200 Hours The objective of this unit is to offer a comprehensive introduction to the fundamental principles of probability and statistics, starting from the basics. It will cover a wide spectrum of data analysis procedures and methodologies. UNIT3- Advanced Predictive Modeling Reference No : Unit 3 - J/650/5564 Credit : 20 || TQT : 200 Hours You will become acquainted with key predictive modelling methods and their underlying foundational principles in this unit. UNIT4- Data Analysis and Visualisation Reference No : Unit 4 - K/650/5565 Credit : 20 || TQT : 200 Hours This unit serves as a crucial foundation for grasping the core concepts of the data analysis process, encompassing data collection, data cleansing, data analysis, and the effective communication of insights through visualisations and dashboard tools. UNIT5- Data Mining Machine Learning and Artificial Intelligence Reference No : Unit 5 - J/650/5573 Credit : 20 || TQT : 200 Hours The primary aim of this unit is to provide an introduction to the scientific principles underpinning machine intelligence and to explore the philosophical discourse surrounding the endeavour to simulate human intelligence for addressing real-world challenges. UNIT6- Advanced Computing Research Methods Reference No : Unit 6 - L/650/5566 Credit : 20 || TQT : 200 Hours This unit aims to enhance learners' skills in preparing for diverse forms of academic computing research by guiding them through creating and designing a research proposal. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.

Data Science with Python bundle course teaches you everything on the Data Science with Python topic thoroughly from scratch so you can achieve a certificate for free to showcase your achievement in professional life. This Data Science with Python bundle course is a comprehensive course designed to provide a detailed understanding of the nature of the Data Science with Python related sector and your key roles within it.The training materials of this Data Science with Python course are available online for you to learn at your own pace and fast-track your career with ease. Key Features of Data Science with Python Bundle CPD Accredited Data Science with Python Course Instant PDF certificate Fully online, interactive Data Science with Pythoncourse Self-paced learning and laptop, tablet, smartphone-friendly 24/7 Learning Assistance Discounts on bulk purchases Enrol now in this Data Science with Python Bundle course to excel! To become successful in your profession, you must have a specific set of Data Science with Python skills to succeed in today's competitive world. In this in-depth Data Science with Pythontraining course, you will develop the most in-demand Data Science with Python skills to kickstart your career, as well as upgrade your existing knowledge & skills. Data Science with Python Curriculum Course 01: Data Analytics Course 02: Python Programming: Beginner To Expert Course 03: Complete Java Course 04: Machine Learning Basics Accreditation This Data Science with Python bundle courses are CPD accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Certification Once you've successfully completed your Data Science with Python course, you will immediately be sent a digital certificate. Also, you can have your printed certificate delivered by post (shipping cost £3.99). CPD 50 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This course is ideal for all employees or anyone who genuinely wishes to learn more about Data Science with Python basics. Requirements No prior degree or experience is required to enrol in this course. Career path This Data Science with Python Course will help you to explore avariety of career paths in the related industry. Certificates Digital certificate Digital certificate - Included Hardcopy Certificate Hard copy certificate - Included Hardcopy Certificate (UK Delivery): For those who wish to have a physical token of their achievement, we offer a high-quality, printed certificate. This hardcopy certificate is also provided free of charge. However, please note that delivery fees apply. If your shipping address is within the United Kingdom, the delivery fee will be only £3.99. Hardcopy Certificate (International Delivery): For all international addresses outside of the United Kingdom, the delivery fee for a hardcopy certificate will be only £10.

Are you looking to enhance your Python- Beginner to Advance skills? If yes, then you have come to the right place. Our comprehensive course on Python- Beginner to Advance will assist you in producing the best possible outcome by mastering the Python- Beginner to Advance skills. The Python- Beginner to Advance course is for those who want to be successful. In the Python- Beginner to Advance course, you will learn the essential knowledge needed to become well versed in Python- Beginner to Advance. Our course starts with the basics of Python- Beginner to Advance and gradually progresses towards advanced topics. Therefore, each lesson of this Python- Beginner to Advance course is intuitive and easy to understand. Why would you choose the Python- Beginner to Advance course from Compliance Central: Lifetime access to Python- Beginner to Advance course materials Full tutor support is available from Monday to Friday with the Python- Beginner to Advance course Learn Python- Beginner to Advance skills at your own pace from the comfort of your home Gain a complete understanding of Python- Beginner to Advance course Accessible, informative Python- Beginner to Advance learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Python- Beginner to Advance course Study Python- Beginner to Advance in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Python- Beginner to Advance course Curriculum Breakdown of the Python- Beginner to Advance Course Introduction Curriculum Overview What's New command line basics python installation Pycham-ce ide installation Setting up environment Running python code git and github overview Python Data Types Python Arithmetic Operators Numbers Variable Assignments Strings Introduction Indexing and Slicing with Strings String Properties and Methods CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Python- Beginner to Advance course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Python- Beginner to Advance. It is also great for professionals who are already working in Python- Beginner to Advance and want to get promoted at work. Requirements To enrol in this Python- Beginner to Advance course, all you need is a basic understanding of the English Language and an internet connection. Career path The Python- Beginner to Advance course will enhance your knowledge and improve your confidence in exploring opportunities in various sectors. Python Developer: £35,000 to £70,000 per year Data Analyst: £25,000 to £55,000 per year Machine Learning Engineer: £45,000 to £85,000 per year Software Engineer: £40,000 to £75,000 per year Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99 each

Overview This comprehensive course on Building Big Data Pipelines with PySpark MongoDB and Bokeh will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Building Big Data Pipelines with PySpark MongoDB and Bokeh 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? 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 Building Big Data Pipelines with PySpark MongoDB and Bokeh. It is available to all students, of all academic backgrounds. Requirements Our Building Big Data Pipelines with PySpark MongoDB and Bokeh 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 7 sections • 25 lectures • 05:04:00 total length •Introduction: 00:10:00 •Python Installation: 00:03:00 •Installing Third Party Libraries: 00:03:00 •Installing Apache Spark: 00:12:00 •Installing Java (Optional): 00:05:00 •Testing Apache Spark Installation: 00:06:00 •Installing MongoDB: 00:04:00 •Installing NoSQL Booster for MongoDB: 00:07:00 •Integrating PySpark with Jupyter Notebook: 00:05:00 •Data Extraction: 00:19:00 •Data Transformation: 00:15:00 •Loading Data into MongoDB: 00:13:00 •Data Pre-processing: 00:19:00 •Building the Predictive Model: 00:12:00 •Creating the Prediction Dataset: 00:08:00 •Loading the Data Sources from MongoDB: 00:17:00 •Creating a Map Plot: 00:33:00 •Creating a Bar Chart: 00:09:00 •Creating a Magnitude Plot: 00:15:00 •Creating a Grid Plot: 00:09:00 •Installing Visual Studio Code: 00:05:00 •Creating the PySpark ETL Script: 00:24:00 •Creating the Machine Learning Script: 00:30:00 •Creating the Dashboard Server: 00:21:00 •Source Code and Notebook: 00:00:00

Embark on a transformative journey into Python programming, ranging from fundamentals to advanced concepts like NumPy and Pandas. This course not only equips you with a comprehensive understanding of Python but also guides you through practical applications such as scripting and library usage. With the demand for Python expertise soaring in the UK, where Python Developers earn an average of £45,000 per year, this course opens doors to a realm of opportunities. Join us and immerse yourself in the dynamic world of Python, unlocking a pathway to a lucrative career in programming. ________________________________________________________________________ Key Features: CPD Certified Diploma in Python Programming: Beginner To Expert With Complete Career Guide 10 Instant e-certificate and hard copy dispatch by next working day Fully online, interactive course with audio voiceover Developed by qualified professionals in the field Self-paced learning and laptop, tablet, smartphone-friendly 24/7 Learning Assistance Discounts on bulk purchases Course Curriculum: Module 01: Introduction to Python Programming from A-Z Module 02: Getting Familiar with Python Module 03: Basic Data Types Module 04: Python Operators Module 05: Advanced Data Types Module 06: Control Flow Part 1 Module 07: Control Flow Part 2 Module 08: Python Functions Module 09: User Input and Error Handling Module 10: Python Advanced Functions Module 11: Python Scripting and Libraries Module 12: NumPy Module 13: Pandas Module 14: Introduction to OOP Module 15: Advanced OOP Module 16: Starting a Career in Python ________________________________________________________________________ Complete Career Guide for Python Programming: Beginner To Expert(A to Z) This isn't just a course; it's your ticket to thriving in the sector and your roadmap to the Programming. In addition to mastering the essentials of Programming, you'll also gain valuable skills in CV writing, job searching, communication, leadership, and project management. These 9 complementary courses are designed to empower you at every stage of your journey. Stand out in your career, from crafting a winning CV to excelling in interviews. Develop the leadership skills to inspire your team and efficiently manage projects. This holistic approach ensures you're not just job-ready but career-ready. Enrol today, and let's build your success story together in Programming. Your dream career starts here! List of career guide courses included in Python Programming: Beginner To Expert With Complete Career Guide: Course 01: Professional CV Writing and Job Searching Course 02: Communication Skills Training Course 03: Career Development Training Course 04: Time Management Course 05: Returning to Work Training Course 06: Level 3 Diploma in Project Management Course 07: Leadership Skills Course 08: Body Language Course 09: Interview and Recruitment ________________________________________________________________________ Learning Outcomes: Understand Python programming fundamentals comprehensively. Apply Python operators effectively in program development. Demonstrate proficiency in handling basic and advanced data types. Implement control flow structures for efficient program execution. Develop and utilize Python functions, including advanced concepts. Gain practical skills in scripting, using libraries, and mastering OOP. ________________________________________________________________________ Accreditation All of our courses, including the Python Programming: Beginner To Expert With Complete Career Guide, are fully accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Certification Once you've successfully completed your Python Programming: Beginner To Expert With Complete Career Guide, you will immediately be sent your digital certificates. Also, you can have your printed certificate delivered by post (shipping cost £3.99). Our certifications have no expiry dates, although we recommend renewing them every 12 months. Assessment At the end of the courses, there will be an online assessment, which you will need to pass to complete the course. Answers are marked instantly and automatically, allowing you to know straight away whether you have passed. If you haven't, there's no limit on the number of times you can take the final exam. All this is included in the one-time fee you paid for the course itself. CPD 100 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals new to programming seeking a thorough Python foundation. Students or professionals aiming to enhance data handling skills. Aspiring developers interested in scripting and library usage. Those pursuing a career in Python and object-oriented programming. Career path Python Developer - £35K to 55K/year. Data Analyst - £30K to 45K/year. Software Engineer - £40K to 65K/year. Machine Learning Engineer - £45K to 75K/year. Data Scientist - £50K to 80K/year. Certificates 10 CPD Accredited e-Certificates Digital certificate - Included 10 CPD Accredited Hard Copy Certificates Hard copy certificate - Included

Scala is doubtless one of the most in-demand skills for data scientists and data engineers. This competitive course will teach you the essential concepts and methodologies of Scala with a lot of practical implementations.

Learn Python Programming using a Step By Step Approach with 200+ code examples.

This course focuses on Python 3 and uses modern Python 3.7 and Python 3.8. It is designed to support Python application development on Windows, macOS, and Linux. As Python 2 is no longer maintained by the Python development team, and there are no more security updates, the focus has now shifted to using Python 3.

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

Learn to use cutting-edge language models ChatGPT, Dalle-2, and Midjourney to create high-quality written content and generative art in this course. Discover how to fine-tune these models for specific tasks and explore the ethical implications and future-proofing strategies for using AI in your work.