568 Machine Learning (ML) courses

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

Overview This comprehensive course on Microsoft Azure Cloud Concepts will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Microsoft Azure Cloud Concepts 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 Microsoft Azure Cloud Concepts. It is available to all students, of all academic backgrounds. Requirements Our Microsoft Azure Cloud Concepts 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 1 sections • 29 lectures • 03:33:00 total length •Unit 01: What will you learn and Cloud Concepts: 00:18:00 •Unit 02: Core Azure architectural components: 00:18:00 •Unit 03: LAB Create a Windows and Linux VM Computer: 00:10:00 •Unit 04: LAB Container creation: 00:04:00 •Unit 05: Storage with Azure: 00:04:00 •Unit 06: LAB Create a storage account: 00:07:00 •Unit 07: Network concepts: 00:03:00 •Unit 08: Lab Network Peering: 00:16:00 •Unit 09: Lab scale set: 00:11:00 •Unit 10: Marketspace and Serverless: 00:07:00 •Unit 11: Event HUB and Logic APPS: 00:07:00 •Unit 12: DevOps Overview: 00:04:00 •Unit 13: Azure Databases Overview: 00:04:00 •Unit 14: Lab SQL: 00:08:00 •Unit 15: What are AI and machine learning: 00:10:00 •Unit 16: Powershell and CLI: 00:09:00 •Unit 17: Azure Advisor: 00:05:00 •Unit 18: Review Core Azure: 00:04:00 •Unit 19: Azure security compliance and trust: 00:03:00 •Unit 20: Lab DDOS and NSGs: 00:07:00 •Unit 21: Authentication and Authorisation: 00:07:00 •Unit 22: Azure security centre: 00:06:00 •Unit 23: LAB Azure key vault and AIP overview: 00:06:00 •Unit 24: Azure Advanced Threat Protection (Azure ATP): 00:06:00 •Unit 25: Azure monitoring: 00:05:00 •Unit 26: Manage Azure Governance: 00:07:00 •Unit 27: Azure privacy and compliance: 00:04:00 •Unit 28: Summary: 00:03:00 •Unit 29: Azure Pricing and support: 00:10:00

Overview The demand for skilled cybersecurity professionals is soaring in today's digital landscape. The CompTIA CySA+ Cybersecurity Analyst (CS0-002) course is your gateway to a lucrative and rewarding career in this high-demand industry. This course delves deep into various aspects of cybersecurity, from threat analysis and vulnerability identification to incident response and digital forensics. It's designed to ensure you're ready to excel in the field. This course covers various topics, including threat intelligence, vulnerability identification, incident response, and forensics analysis.  With 60+ hours of engaging content, our expert instructors will equip you with the knowledge and skills required to excel in the CompTIA CySA+ certification exam and kickstart your career in cybersecurity. Enrol in the CompTIA CySA+ Cybersecurity Analyst (CS0-002) course today and secure your future in this high-demand industry! 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 CompTIA CySA+ Cybersecurity Analyst (CS0-002). It is available to all students, of all academic backgrounds. Requirements Our CompTIA CySA+ Cybersecurity Analyst (CS0-002) 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 22 sections • 96 lectures • 11:35:00 total length •Introduction: 00:02:00 •All about the Exam: 00:08:00 •What's New on the CompTIA CySA+ Exam?: 00:05:00 •Meet the Instructors: 00:02:00 •Thinking like the Enemy: 00:09:00 •Tools of the Trade: 00:08:00 •Intelligence Sources and Confidence Levels: 00:08:00 •Threat Indicators and Actors: 00:08:00 •Threat Trends: 00:07:00 •Intelligence Cycle and ISACs: 00:06:00 •Attack Frameworks: 00:06:00 •Threat Research: 00:11:00 •Threat Modeling and Intelligence Sharing: 00:06:00 •Vulnerability Identification: 00:07:00 •Scanning Parameters and Criteria: 00:09:00 •Scanning Special Considerations: 00:06:00 •Validation: 00:03:00 •Remediation and Mitigation: 00:08:00 •Inhibitors to Remediation: 00:07:00 •Web Applications Scanners, Part 1: 00:10:00 •Web Applications Scanners, Part 2: 00:05:00 •Scanning: 00:06:00 •Configuring and Executing Scans: 00:08:00 •Vulnerability Scanning: 00:10:00 •Reverse Engineering: 00:08:00 •Enumeration: 00:06:00 •Wireless Assessment Tools: 00:08:00 •Cloud Assessment Tools: 00:04:00 •Mobile and IoT: 00:10:00 •Embedded and Firmware Systems (RTOS, SoC, and FPGA): 00:09:00 •Access and Vehicles Risk: 00:08:00 •Automation and Control Risk: 00:10:00 •Cloud Models: 00:07:00 •Remote Service Invocation (FaaS, IaC, API): 00:10:00 •Cloud Vulnerabilities: 00:06:00 •Injection and Overflow Attacks: 00:09:00 •Injection and Overflow Attacks: 00:09:00 •Exploits: 00:08:00 •Application Vulnerabilities, Part 1: 00:08:00 •Application Vulnerabilities, Part 2: 00:07:00 •Network Architecture and Asset Management: 00:09:00 •Protecting Your Territory: 00:05:00 •Identity and Access Management: 00:11:00 •Encryption and Active Defense: 00:08:00 •Platforms: 00:07:00 •SOA and DevSecOps: 00:09:00 •Secure Software Development: 00:08:00 •Best Coding Practices: 00:04:00 •Trusted Hardware: 00:10:00 •Hardware Encryption: 00:04:00 •Hardware Security: 00:08:00 •Data Analytics: 00:10:00 •Endpoint Security: 00:08:00 •Recon Results, Part 1: 00:13:00 •Recon Results, Part 2: 00:05:00 •Impact Analysis: 00:05:00 •Collective Tools: 00:09:00 •Query Writing: 00:07:00 •E-mail Analysis, Part 1: 00:10:00 •E-mail Analysis, Part 2: 00:08:00 •Permissions: 00:09:00 •Firewalls: 00:08:00 •Intrusion Prevention Rules: 00:05:00 •DLP and Endpoint Detection: 00:05:00 •Threat Hunting and the Hypothesis: 00:06:00 •Threat Hunting Process: 00:07:00 •Results and Benefits: 00:05:00 •Workflow and Scripting: 00:07:00 •API and Malware Signature Creation: 00:08:00 •Threat Feeds and Machine Learning: 00:06:00 •Protocols, Standards, and Software Engineering: 00:05:00 •IR Roles and Responsibilities: 00:08:00 •IR Active Preparation: 00:10:00 •Incident Response Process: 00:07:00 •Network Symptoms: 00:04:00 •Host Symptoms: 00:08:00 •Application Symptoms: 00:04:00 •Digital Forensics: 00:10:00 •Seizure and Acquisitions: 00:05:00 •Forensics Acquisition Tools: 00:09:00 •Mobile, Virtualization, and Cloud: 00:06:00 •Forensics Analysis, Part 1: 00:04:00 •Forensics Analysis, Part 2: 00:08:00 •Packet Capture: 00:12:00 •Data Privacy and Security: 00:06:00 •Nontechnical Controls: 00:09:00 •Technical Controls: 00:08:00 •Business Impact Analysis: 00:05:00 •Risk Identification: 00:05:00 •Risk Calculation and Communication: 00:06:00 •Training: 00:04:00 •Supply Chain Assessment: 00:04:00 •Frameworks: 00:13:00 •Policies and Procedures: 00:05:00 •Controls and Procedures: 00:08:00 •Verification: 00:06:00

Dive into the transformative world of Artificial Intelligence through the course titled 'Foundations of Artificial Intelligence: Building Intelligent Systems.' This comprehensive curriculum sweeps across an array of subjects, from the rudimentary introduction to AI to the intricate nuances of building AI applications. Embrace a holistic understanding of core modules like Machine Learning, Natural Language Processing, and Robotics. The content, framed meticulously, beckons those inquisitive minds eager to craft, innovate, and change the world with AI's limitless possibilities. Deepen your conceptual clarity with two-part modules that delve into Knowledge Representation and Machine Learning, ensuring that learners grasp intricate details without feeling overwhelmed. With sections dedicated to Computer Vision and Deep Learning, individuals will find themselves proficiently navigating the vibrant ecosystems these technologies encompass. Finally, a spotlight on AI applications ensures that learners not only acquire theoretical wisdom but also grasp how AI integrates into real-world scenarios. By the culmination of this course, participants will stand at the forefront of AI innovations, armed with the acumen to shape a future where intelligent systems intertwine seamlessly with our daily lives. This foundation lays the groundwork for boundless exploration in the Artificial Intelligence realm Learning Outcomes Upon completion of this course, participants will be able to: Gain comprehensive insights into the fundamental principles of Artificial Intelligence. Understand the critical mathematical concepts underpinning AI technologies. Develop proficiency in various AI knowledge representation methods. Acquire a solid foundation in Machine Learning, Deep Learning, and Natural Language Processing techniques. Familiarise with the applications and integrations of AI in Robotics and Computer Vision. Why buy this Foundations of Artificial Intelligence: Building Intelligent Systems? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Foundations of Artificial Intelligence: Building Intelligent Systems there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Foundations of Artificial Intelligence: Building Intelligent Systems course for? This Foundations of Artificial Intelligence: Building Intelligent Systems does not require you to have any prior qualifications or experience. You can just enrol and start learning. Aspiring AI enthusiasts keen on building a robust foundation in the subject. Technologists aiming to pivot into AI-centric roles. Researchers eager to enhance their knowledge spectrum in intelligent systems. University students studying computer science or related disciplines, looking to supplement their academic pursuits. Entrepreneurs eyeing opportunities in AI-driven ventures. Prerequisites This Foundations of Artificial Intelligence: Building Intelligent Systems does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Foundations of Artificial Intelligence: Building Intelligent Systems was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path AI Research Scientist - Average Salary Range: £60,000 - £85,000 per annum Machine Learning Engineer - Average Salary Range: £55,000 - £80,000 per annum NLP Specialist - Average Salary Range: £50,000 - £75,000 per annum Computer Vision Engineer - Average Salary Range: £52,000 - £77,000 per annum Robotics Engineer - Average Salary Range: £48,000 - £73,000 per annum AI Application Developer - Average Salary Range: £54,000 - £79,000 per annum Course Curriculum Module 01: Introduction to Artificial Intelligence Introduction to Artificial Intelligence 00:21:00 Module 02: Mathematics for AI Mathematics for AI 00:17:00 Module 03: Knowledge Representation in AI - Part 1 Knowledge Representation in AI - Part 1 00:18:00 Module 04: Knowledge Representation in AI - Part 2 Knowledge Representation in AI - Part 2 00:16:00 Module 05: Machine Learning - Part 1 Machine Learning - Part 1 00:16:00 Module 06: Machine Learning - Part 2 Machine Learning - Part 2 00:15:00 Module 07: Deep Learning Deep Learning 00:16:00 Module 08: Natural Language Processing Natural Language Processing 00:22:00 Module 09: Computer Vision Computer Vision 00:14:00 Module 10: Robotics Robotics 00:18:00 Module 11: Building AI Applications Building AI Applications 00:24:00

Overview This comprehensive course on Data Visualization and Reporting with Power BI will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Visualization and Reporting with Power BI 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 Data Visualization and Reporting with Power BI. It is available to all students, of all academic backgrounds. Requirements Our Data Visualization and Reporting with Power BI 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 15 sections • 140 lectures • 14:25:00 total length •Welcome!: 00:01:00 •What is Power BI?: 00:03:00 •Download & Installing Power BI Desktop: 00:04:00 •Getting to know the interface: 00:03:00 •Mini Project: Transform Data: 00:07:00 •Mini Project: Visualize Data: 00:05:00 •Mini Project: Creating a Data Model: 00:07:00 •Course Outline: What will you learn in this course?: 00:05:00 •How to learn best with this course?: 00:03:00 •Creating our initial project file: 00:04:00 •Working with the attached project files: 00:04:00 •Exploring the Query Editor: 00:06:00 •Connecting to our data source: 00:07:00 •Editing rows: 00:08:00 •Changing data types: 00:08:00 •Replacing values: 00:03:00 •Close & Apply: 00:03:00 •Connecting to a csv file: 00:03:00 •Connecting to a web page: 00:05:00 •Extracting characters: 00:06:00 •Splitting & merging columns: 00:09:00 •Creating conditional columns: 00:06:00 •Creating columns from examples: 00:09:00 •Merging Queries: 00:17:00 •Pivoting & Unpivoting: 00:06:00 •Appending Queries: 00:08:00 •Practice & Solution: Population table: 00:15:00 •The Fact-Dimension-Model: 00:09:00 •Practice: Load the dimension table: 00:04:00 •Organizing our queries in groups: 00:03:00 •Entering data manually: 00:05:00 •Creating an index column: 00:03:00 •Workflow & more transformations: 00:05:00 •Module summary: 00:05:00 •Exercise 1 - Instruction: 00:02:00 •Exercise 1 - Exercise Solution: 00:11:00 •Advanced Editor - Best practices: 00:09:00 •Performance: References vs. Duplicating: 00:10:00 •Performance: Enable / Disable Load & Report Refresh: 00:05:00 •Group by: 00:05:00 •Mathematical Operations: 00:05:00 •Run R Script: 00:15:00 •Using Parameters to dynamically transform data: 00:06:00 •M formula language: Basics: 00:07:00 •M formula language: Values, Lists & Tables: 00:14:00 •M formula language: Functions: 00:13:00 •M formula language: More functions & steps: 00:05:00 •Exercise 2 - Instructions: 00:01:00 •Exercise 2 - solution: 00:05:00 •Understanding the relationship: 00:05:00 •Create & edit relationships: 00:06:00 •One-to-many & one-to-one relationship: 00:06:00 •Many-to-many (m:n) relationship: 00:08:00 •Cross filter direction: 00:06:00 •Activate & deactivate relationships: 00:06:00 •Model summary: 00:03:00 •Exercise 3 Create Model: 00:02:00 •Exercise 3 Solution: 00:02:00 •Our first visual: 00:08:00 •The format tab: 00:12:00 •Understanding tables: 00:10:00 •Conditional formatting: 00:09:00 •The Pie Chart: 00:06:00 •All about the filter visual: 00:13:00 •The filter pane for developers: 00:09:00 •Cross filtering & edit interactions: 00:04:00 •Syncing slicers across pages: 00:07:00 •Creating drill downs: 00:08:00 •Creating drill throughs: 00:07:00 •The tree map visual: 00:07:00 •The decomposition tree: 00:05:00 •Understanding the matrix visual: 00:05:00 •Editing pages: 00:07:00 •Buttons & Actions: 00:09:00 •Bookmarks to customize your report: 00:10:00 •Analytics and Forecasts with line charts: 00:10:00 •Working with custom visuals: 00:07:00 •Get data using R Script & R Script visual: 00:08:00 •Asking questions - Q&A visual: 00:04:00 •Wrap up - data visualization: 00:08:00 •Python in Power BI - Plan of attack: 00:03:00 •Setting up Python for Power BI: 00:03:00 •Transforming data using Python: 00:11:00 •Creating visualizations using Python: 00:08:00 •Violin plots, pair plots & ridge plots using Python: 00:15:00 •Machine learning (BayesTextAnalyzer) using Python: 00:00:00 •Performance & Troubleshooting: 00:03:00 •Introduction: 00:01:00 •Show Empathy & Identify the Requirement: 00:03:00 •Finding the Most Suitable KPI's: 00:02:00 •Choose an Effective Visualization: 00:04:00 •Make Use of Natural Reading Pattern: 00:03:00 •Tell a Story Using Visual Cues: 00:05:00 •Avoid Chaos & Group Information: 00:02:00 •Warp Up - Storytelling with Data: 00:02:00 •Introduction: 00:03:00 •The project data: 00:04:00 •Measures vs. Calculated Columns: 00:15:00 •Automatically creating a date table in DAX: 00:08:00 •CALENDAR: 00:05:00 •Creating a complete date table with features: 00:04:00 •Creating key measure table: 00:03:00 •Aggregation functions: 00:06:00 •The different versions of COUNT: 00:14:00 •SUMX - Row based calculations: 00:09:00 •CALCULATE - The basics: 00:11:00 •Changing the context with FILTER: 00:07:00 •ALL: 00:08:00 •ALL SELECTED: 00:03:00 •ALL EXCEPT: 00:07:00 •How to go on now?: 00:03:00 •Power BI Pro vs Premium & Signing up: 00:04:00 •Exploring the interface: 00:04:00 •Discovering your workspace: 00:03:00 •Connecting Power BI Desktop & Cloud: 00:04:00 •Understanding datasets & reports: 00:03:00 •Working on reports: 00:04:00 •Updating reports from Power BI Desktop: 00:04:00 •Creating and working with workspaces: 00:07:00 •Installing & using a data gateway: 00:13:00 •Get Quick Insights: 00:03:00 •Creating dashboards: 00:04:00 •Sharing our results through Apps: 00:10:00 •Power BI Mobile App: 00:05:00 •Creating the layout for the Mobile App: 00:04:00 •Wrap up - Power BI Cloud: 00:07:00 •Introduction: 00:03:00 •Creating a Row-Level Security: 00:05:00 •Row-Level Security in the Cloud: 00:04:00 •Row-Level Security & Data Model: 00:05:00 •Dynamic Row-Level Security: 00:07:00 •Dynamic Many-to-Many RLS: 00:04:00 •Hierarchical Row-Level Security: 00:13:00 •JSON & REST API: 00:10:00 •Setting up a local MySQL database: 00:14:00 •Connecting to a MySQL database in Power BI: 00:05:00 •Connecting to a SQL database (PostgreSQL): 00:05:00 •Congratulations & next steps: 00:06:00 •The End: 00:01:00 •Resources - Data Visualization and Reporting with Power BI: 00:00:00

Overview This comprehensive course on Complete Microsoft Power BI 2021 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Complete Microsoft Power BI 2021 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 Complete Microsoft Power BI 2021. It is available to all students, of all academic backgrounds. Requirements Our Complete Microsoft Power BI 2021 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 15 sections • 140 lectures • 14:25:00 total length •Welcome!: 00:01:00 •What is Power BI?: 00:03:00 •Download & Installing Power BI Desktop: 00:04:00 •Getting to know the interface: 00:03:00 •Mini Project: Transform Data: 00:07:00 •Mini Project: Visualize Data: 00:05:00 •Mini Project: Creating a Data Model: 00:07:00 •Course Outline: What will you learn in this course?: 00:05:00 •How to learn best with this course?: 00:03:00 •Creating our initial project file: 00:04:00 •Working with the attached project files: 00:04:00 •Exploring the Query Editor: 00:06:00 •Connecting to our data source: 00:07:00 •Editing rows: 00:08:00 •Changing data types: 00:08:00 •Replacing values: 00:03:00 •Close & Apply: 00:03:00 •Connecting to a csv file: 00:03:00 •Connecting to a web page: 00:05:00 •Extracting characters: 00:06:00 •Splitting & merging columns: 00:09:00 •Creating conditional columns: 00:06:00 •Creating columns from examples: 00:09:00 •Merging Queries: 00:17:00 •Pivoting & Unpivoting: 00:06:00 •Appending Queries: 00:08:00 •Practice & Solution: Population table: 00:15:00 •The Fact-Dimension-Model: 00:09:00 •Practice: Load the dimension table: 00:04:00 •Organizing our queries in groups: 00:03:00 •Entering data manually: 00:05:00 •Creating an index column: 00:03:00 •Workflow & more transformations: 00:05:00 •Module summary: 00:05:00 •Exercise 1 - Instruction: 00:02:00 •Exercise 1 - Exercise Solution: 00:11:00 •Advanced Editor - Best practices: 00:09:00 •Performance: References vs. Duplicating: 00:10:00 •Performance: Enable / Disable Load & Report Refresh: 00:05:00 •Group by: 00:05:00 •Mathematical Operations: 00:05:00 •Run R Script: 00:15:00 •Using Parameters to dynamically transform data: 00:06:00 •M formula language: Basics: 00:07:00 •M formula language: Values, Lists & Tables: 00:14:00 •M formula language: Functions: 00:13:00 •M formula language: More functions & steps: 00:05:00 •Exercise 2 - Instructions: 00:01:00 •Exercise 2 - solution: 00:05:00 •Understanding the relationship: 00:05:00 •Create & edit relationships: 00:06:00 •One-to-many & one-to-one relationship: 00:06:00 •Many-to-many (m:n) relationship: 00:08:00 •Cross filter direction: 00:06:00 •Activate & deactivate relationships: 00:06:00 •Model summary: 00:03:00 •Exercise 3 Create Model: 00:02:00 •Exercise 3 Solution: 00:02:00 •Our first visual: 00:08:00 •The format tab: 00:12:00 •Understanding tables: 00:10:00 •Conditional formatting: 00:09:00 •The Pie Chart: 00:06:00 •All about the filter visual: 00:13:00 •The filter pane for developers: 00:09:00 •Cross filtering & edit interactions: 00:04:00 •Syncing slicers across pages: 00:07:00 •Creating drill downs: 00:08:00 •Creating drill throughs: 00:07:00 •The tree map visual: 00:07:00 •The decomposition tree: 00:05:00 •Understanding the matrix visual: 00:05:00 •Editing pages: 00:07:00 •Buttons & Actions: 00:09:00 •Bookmarks to customize your report: 00:10:00 •Analytics and Forecasts with line charts: 00:10:00 •Working with custom visuals: 00:07:00 •Get data using R Script & R Script visual: 00:08:00 •Asking questions - Q&A visual: 00:04:00 •Wrap up - data visualization: 00:08:00 •Python in Power BI - Plan of attack: 00:03:00 •Setting up Python for Power BI: 00:03:00 •Transforming data using Python: 00:11:00 •Creating visualizations using Python: 00:08:00 •Violin plots, pair plots & ridge plots using Python: 00:15:00 •Machine learning (BayesTextAnalyzer) using Python: 00:00:00 •Performance & Troubleshooting: 00:03:00 •Introduction: 00:01:00 •Show Empathy & Identify the Requirement: 00:03:00 •Finding the Most Suitable KPI's: 00:02:00 •Choose an Effective Visualization: 00:04:00 •Make Use of Natural Reading Pattern: 00:03:00 •Tell a Story Using Visual Cues: 00:05:00 •Avoid Chaos & Group Information: 00:02:00 •Warp Up - Storytelling with Data: 00:02:00 •Introduction: 00:03:00 •The project data: 00:04:00 •Measures vs. Calculated Columns: 00:15:00 •Automatically creating a date table in DAX: 00:08:00 •CALENDAR: 00:05:00 •Creating a complete date table with features: 00:04:00 •Creating key measure table: 00:03:00 •Aggregation functions: 00:06:00 •The different versions of COUNT: 00:14:00 •SUMX - Row based calculations: 00:09:00 •CALCULATE - The basics: 00:11:00 •Changing the context with FILTER: 00:07:00 •ALL: 00:08:00 •ALL SELECTED: 00:03:00 •ALL EXCEPT: 00:07:00 •How to go on now?: 00:03:00 •Power BI Pro vs Premium & Signing up: 00:04:00 •Exploring the interface: 00:04:00 •Discovering your workspace: 00:03:00 •Connecting Power BI Desktop & Cloud: 00:04:00 •Understanding datasets & reports: 00:03:00 •Working on reports: 00:04:00 •Updating reports from Power BI Desktop: 00:04:00 •Creating and working with workspaces: 00:07:00 •Installing & using a data gateway: 00:13:00 •Get Quick Insights: 00:03:00 •Creating dashboards: 00:04:00 •Sharing our results through Apps: 00:10:00 •Power BI Mobile App: 00:05:00 •Creating the layout for the Mobile App: 00:04:00 •Wrap up - Power BI Cloud: 00:07:00 •Introduction: 00:03:00 •Creating a Row-Level Security: 00:05:00 •Row-Level Security in the Cloud: 00:04:00 •Row-Level Security & Data Model: 00:05:00 •Dynamic Row-Level Security: 00:07:00 •Dynamic Many-to-Many RLS: 00:04:00 •Hierarchical Row-Level Security: 00:13:00 •JSON & REST API: 00:10:00 •Setting up a local MySQL database: 00:14:00 •Connecting to a MySQL database in Power BI: 00:05:00 •Connecting to a SQL database (PostgreSQL): 00:05:00 •Congratulations & next steps: 00:06:00 •The End: 00:01:00 •Resources - Complete Microsoft Power BI 2021: 00:00:00

Overview This comprehensive course on Complete iOS 11 and Swift 4 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Complete iOS 11 and Swift 4 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 Complete iOS 11 and Swift 4. It is available to all students, of all academic backgrounds. Requirements Our Complete iOS 11 and Swift 4 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 13 sections • 177 lectures • 19:08:00 total length •iOS 11 Course Overview: 00:11:00 •Install Xcode 9: 00:07:00 •Xcode 9 Beta 4 Update: 00:09:00 •App: Hustle - Your first iOS 11 App: 00:22:00 •Variables, operators, and how computers work: 00:17:00 •Strings in Swift: 00:15:00 •Working with numbers in Swift: 00:20:00 •Swift Functions: 00:23:00 •Booleans: 00:21:00 •Constants: 00:10:00 •Array Data Structure in Swift: 00:13:00 •Swift Loops: 00:19:00 •Dictionary Data Structure in Swift: 00:19:00 •Object Oriented Programming in Swift: 00:12:00 •Inheritance: 00:08:00 •Polymorphism: 00:08:00 •Optionals: 00:21:00 •Enumerations: 00:20:00 •Extensions: Part 1: 00:15:00 •Extensions: Part 2: 00:21:00 •Intro to Protocols, Delegates - Numbers Example: 00:13:00 •Intro to Protocols, Delegates Part 2 - Question Generator: 00:18:00 •Protocols, Delegates - Building Color Magic App UI: 00:17:00 •Protocols, Delegates - Using the Delegate Method in Color Magic App: 00:16:00 •Protocols, Delegates - Using Mutating Functions in Types: 00:18:00 •Git and Version Control - The Fun Way!: 00:12:00 •Terminal Basics - Changing Directories: 00:06:00 •Terminal Basics - Creating Directories and Files: 00:05:00 •Terminal Basics - Copying and Renaming Files: 00:09:00 •Terminal Basics - Deleting Files and Directories: 00:06:00 •Git Basics: 00:17:00 •Setting up Github: 00:05:00 •Working with Local and Remote Repositories: 00:11:00 •Handling Git Merge Conflicts: 00:17:00 •App: Swoosh 01 - Creating the Welcome Screen: 00:25:00 •App: Swoosh 02 - Working with Frames: 00:16:00 •App: Swoosh 03 - Intro to Auto Layout: 00:27:00 •App: Swoosh 04 - Working with Stack Views: 00:27:00 •App: Swoosh 05 - Intro to Segues (Changing Screens): 00:10:00 •App: Swoosh 06 - Refactoring in Xcode 9: 00:10:00 •App: Swoosh 07 - Debugging: setValue forUndefinedKey: 00:04:00 •App: Swoosh 08 - Programmatic Segues: 00:09:00 •App: Swoosh 09 - IBActions (Handling Events) and Data Models: 00:16:00 •App: Swoosh 10 - Passing Data Between View Controllers: 00:12:00 •App: Dev Profile 01 - Auto layout for iPhones: 00:22:00 •App: Dev Profile 02 - Auto layout for iPads (Size Classes): 00:20:00 •App: Window Shopper 01 - Custom Text Fields: 00:18:00 •App: Window Shopper 02 - Input Accessory Views: 00:15:00 •App: Window Shopper 03 - Unit Testing our Data: 00:17:00 •App: Window Shopper 04 - Calculation Algorithm: 00:13:00 •App: Window Shopper 05 - Custom Drawing with drawRect: 00:12:00 •App: Coder Swag 01 - Project creation: 00:23:00 •App: Coder Swag 02 - Tableviews, Delegate, and Data Source: 00:33:00 •App: Coder Swag 03 - Collection Views (Grid Layouts): 00:13:00 •App: Coder Swag 04 - Working with Data Models: 00:14:00 •App: Coder Swag 05 - Displaying Data in Collection View Cells: 00:20:00 •Intro to Chat App: 00:04:00 •App: Smack - Project Setup: 00:26:00 •App: Smack - SWReveal: 00:20:00 •App: Smack - ChannelVC UI: 00:25:00 •App: Smack - LoginVC UI: 00:22:00 •App: Smack - CreateAccountVC UI: 00:19:00 •App: Smack - Web request and API: 00:09:00 •App: Smack - Hosting API: 00:20:00 •App: Smack - Locally Hosting API: 00:18:00 •App: Smack - Creating a web request in Xcode: 00:28:00 •App: Smack - Registering a User: 00:16:00 •App: Smack - Logging in a user: 00:20:00 •App: Smack - Creating a user: 00:26:00 •App: Smack - Avatar Picker Part 1: 00:19:00 •App: Smack - Avatar Picker Part 2: 00:20:00 •App: Smack - Generate a Avatar BG Color: 00:26:00 •App: Smack - LoggedIn Interface: 00:23:00 •App: Smack - Profile View: 00:25:00 •App: Smack - Logging in users: 00:23:00 •App: Smack - Getting channels: 00:19:00 •App: Smack - Channels TableView: 00:14:00 •App: Smack - Add Channel VC: 00:19:00 •App: Smack - Sockets and Channels: 00:26:00 •App: Smack - Refining Login Flow: 00:19:00 •App: Smack - Fetching Messages: 00:20:00 •App: Smack - Sending First Message: 00:17:00 •App: Smack - Displaying Chat Messages: 00:18:00 •App: Smack - Sockets and Messages: 00:19:00 •App: Smack - Typing Users: 00:22:00 •App: Smack - Unread Channels: 00:18:00 •Where to go from here: 00:08:00 •I'm Back: 00:08:00 •Intro to App: Pixel City: 00:02:00 •Creating Xcode Project: Pixel City: 00:04:00 •Installing Alamofire / AlamofireImage Cocoapods: 00:07:00 •Building MapVC UI /Conforming to MKMapViewDelegate /Setting Delegate of mapView: 00:15:00 •Requesting Location Services in iOS 11 / Centering Map On User Location: 00:18:00 •Adding UITapGestureRecognizer to Drop Custom Pins on MapView: 00:15:00 •Setting a Custom Map Annotation Color: 00:05:00 •Animating Photos View / Programmatically adding spinner and label subviews: 00:20:00 •Adding UILabel for Pull Up View / Adding UICollectionView Programmatically: 00:17:00 •Getting API Key from Flickr / Using Flickr API URL Format: 00:14:00 •Using Alamofire to Download URLS: 00:21:00 •Using Alamofire to Download Images / Cancelling All Sessions: 00:16:00 •Setting Up UICollectionView / Adding Images / Reloading UICollectionView: 00:10:00 •Building PopVC / Presentation PopVC When UICollectionViewCell is Tapped: 00:16:00 •Adding 3D Touch Peek: 00:15:00 •Challenge 1: 00:02:00 •Setting up developer: 00:10:00 •Implementing Google AdMob: 00:19:00 •Fetching a list of Products: 00:15:00 •Starting an in-app Purchase: 00:09:00 •Testing in-app Purchases: 00:18:00 •Restoring in-app Purchases after App Deletion: 00:09:00 •Intro to App: GoalPost: 00:03:00 •Creating Xcode Project / Project Folders: 00:04:00 •Building GoalsVC: 00:14:00 •Building GoalCell: 00:14:00 •What is Core Data?: 00:06:00 •Creating Goal Core Data Entity and Attributes: 00:08:00 •Displaying Static GoalCells in UITableView / Creating GoalType Enum: 00:10:00 •Building CreateGoalVC: 00:15:00 •Creating a UIViewController Extension: 00:11:00 •Creating a UIView / UIButton Extension: 00:19:00 •Building FinishGoalVC / Passing Data from CreateGoalVC: 00:19:00 •Saving Goal Data to Persistent Store: 00:13:00 •Fixing Dismissal of FinishGoalVC: 00:07:00 •Fetching Data from Persistent Store / Filling UITableView with Fetched Data: 00:16:00 •Removing Objects from Persistent Store using UITableView Delete Action: 00:11:00 •Setting Goal Progress for UITableViewCell: 00:15:00 •Challenge 2: 00:01:00 •Intro to App: Breakpoint: 00:03:00 •Creating Xcode Project / Setting Up Project Folders: 00:05:00 •Creating Firebase Project: 00:11:00 •Setting Up DataService / Creating Firebase Database Users: 00:11:00 •Building AuthVC and LoginVC in Interface Builder: 00:18:00 •Creating InsetTextField and ShadowView Subclasses: 00:18:00 •Setting up AuthService: 00:13:00 •Building FeedVC and GroupsVC in Interface Builder: 00:16:00 •Presenting LoginVC from AppDelegate / Allowing Login with Email: 00:22:00 •Building MeVC and Adding to UITabBarController: 00:10:00 •Creating CreatePostVC and Uploading Posts to Firebase: 00:20:00 •Creating UIView Extension for Binding Views to Keyboard: 00:15:00 •Building FeedCell: 00:10:00 •Writing the Message Model and Getting All Feed Messages from Firebase: 00:21:00 •Converting UIDs into Emails and Reversing the Order of a TableView: 00:20:00 •Creating CreateGroupVC and Connecting @IBOutlets/Actions: 00:15:00 •Creating UserCell: 00:16:00 •Searching for Email Accounts to Add to Group: 00:19:00 •Adding Users to Group with didSelectRowAt indexPath: 00:21:00 •Creating Groups and pushing them to Firebase: 00:16:00 •Creating GroupCell: 00:15:00 •Creating Group Model and Getting All Groups from Firebase: 00:19:00 •Building GroupFeedVC: 00:18:00 •Initializing Group Data for a Group and Presenting on GroupFeedVC: 00:16:00 •Downloading All Message for a Group and Animating Upon New Message: 00:24:00 •Creating a UIViewController Extension for Presenting GroupFeedVC: 00:07:00 •Challenge 3: 00:02:00 •Intro to app: 00:02:00 •Intro to CoreML: 00:05:00 •What is machine learning?: 00:08:00 •Creating Xcode 9 project: 00:03:00 •Building UI: 00:18:00 •AVFoundation: 00:18:00 •Tap gestures to take snapshot on item: 00:11:00 •Core ML Xcode 9 Beta 4 Update / Fix Preview Photo Crash: 00:03:00 •Downloading CoreML models: 00:21:00 •Adding UI controls for flash control: 00:07:00 •Training your app to speak what it sees: 00:18:00 •App: RampUp - Intro to ARKit App: 00:02:00 •App: RampUp - Resources: 00:04:00 •App: RampUp - Project creation: 00:11:00 •App: RampUp - SceneKit, 3D models: 00:11:00 •App: RampUp - Ramp picker popover: 00:14:00 •App: RampUp - 3D models in SceneKit for popover: 00:18:00 •App: RampUp - 3D models in SceneKit for popover part 2: 00:12:00 •App: RampUp - Detecting taps on 3D objects: 00:17:00 •App: RampUp - Placing ramps in ARKit: 00:24:00 •App: RampUp - Moving objects in 3D space in augmented reality: 00:20:00 •ARKit - where to go next: 00:04:00 •Assignment - Complete iOS 11 and Swift 4: 00:00:00

Everywhere, from tiny businesses to major corporations, needs people skilled in SQL. In light of this, our online training course has been developed to help you succeed by equipping you with all the necessary skills. The importance of mastering SQL increases if you're looking for your first job in the data industry. You will learn about topics such as SQL fundamentals, data wrangling, SQL analysis, AB testing, distributed computing with Apache Spark, Delta Lake, and more through four increasingly more challenging SQL projects with data science applications. These subjects will equip you with the skills necessary to use SQL creatively for data analysis and exploration, write queries quickly, produce datasets for data analysis, conduct feature engineering, integrate SQL with other data analysis and machine learning toolsets, and work with unstructured data. This Specialisation is designed for a learner with little or no prior coding expertise who wants to become proficient with SQL queries. Experts have meticulously planned out the curriculum for the SQL Skills Training course with years of expertise. As a result, you will find it simple to learn the course material. Learning outcome After finishing the course, you'll Learn to utilise the tools for view creation Become familiar with updating columns and indexed views Be able to test and debug Be able to search a database using SQL Become more familiar with inline table-valued functions Learn the fundamentals of transactions and multiple statements Why Prefer US? Opportunity to earn a certificate accredited by CPD after completing this course Student ID card with amazing discounts - completely for FREE! (£10 postal charges will be applicable for international delivery) Standards-aligned lesson planning Innovative and engaging content and activities Assessments that measure higher-level thinking and skills Complete the program in your own time, at your own pace Each of our students gets full 24/7 tutor support *** Course Curriculum *** SQL Programming Course Module 01: Course Introduction Introduction Course Curriculum Overview Overview of Databases Module 02: SQL Environment Setup MySQL Installation MySQL Workbench Installation Connecting to MySQL using Console Module 03: SQL Statement Basics Overview of Challenges SQL Statement Basic SELECT Statement SELECT DISTINCT Column AS Statement COUNT built-in Method usage SELECT WHERE Clause - Part One SELECT WHERE Clause - Part Two Statement Basic Limit Clause Statement Using BETWEEN with Same Column Data How to Apply IN Operator Wildcard Characters with LIKE and ILIKE Module 04: GROUP BY Statements Overview of GROUP BY Aggregation function SUM() Aggregation MIN() and MAX() GROUP BY - One GROUP BY - Two HAVING Clause Module 05: JOINS Overview of JOINS Introduction to JOINS AS Statement table INNER Joins FULL Outer Join LEFT Outer JOIN RIGHT JOIN Union Module 06: Advanced SQL Commands / Statements Timestamps EXTRACT from timestamp Mathematical Functions String Functions SUBQUERY Module 07: Creating Database and Tables Basic of Database and Tables Data Types Primary key and Foreign key Create Table in SQL Script Insert Update Delete Alter Table Drop-Table NOT NULL Constraint UNIQUE Constraint Module 08: Databases and Tables Creating a Database backup 10a Overview of Databases and Tables 10c Restoring a Database CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The course can be helpful for anyone working in the SQL fields, whether self-employed or employed, regardless of their career level. Requirements You will not need any prior background or expertise to enrol in this course. Career path The vocation of SQL Skills Training moves very quickly but pays well. This position provides unparalleled satisfaction. This is your opportunity to learn more and start changing things. Query Language Developer Server Database Manager Python Developer Technical Consultant Project Implementation Manager Software Developer (SQL) Certificates Certificate of completion Digital certificate - £10

Quick Data Science Approach from Scratch is an innovatively structured course designed to introduce learners to the fascinating world of data science. The course commences with an enlightening introduction, setting the stage for a deep dive into the essence and significance of data science in the modern era. Learners are guided through a landscape of insights, where misconceptions about data science are addressed and clarified, paving the way for a clear and accurate understanding of the field. In the second section, the course shifts its focus to pivotal data science concepts. Beginning with an exploration of data types and variables, learners gain a solid foundation in handling various data formats. The journey then leads to mastering descriptive analysis, a critical skill for interpreting and understanding data trends. Learners will also navigate through the intricate processes of data cleaning and feature engineering, essential skills for refining and optimizing data for analysis. The concept of 'Data Thinking Development' is introduced, fostering a mindset that is crucial for effective data science practice. The final section offers an immersive experience in applying these skills to a real-world scenario. Here, learners engage in defining a problem, choosing suitable algorithms, and developing predictive models. This practical application is designed to cement the theoretical knowledge acquired and enhance problem-solving skills in data science. Learning Outcomes Build a foundational understanding of data science and its practical relevance. Develop proficiency in managing various data types and conducting descriptive analysis. Learn and implement effective data cleaning and feature engineering techniques. Cultivate a 'data thinking' approach for insightful data analysis. Apply data science methodologies to real-life problems using algorithmic and predictive techniques. Why choose this Quick Data Science Approach from Scratch course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Quick Data Science Approach from Scratch course for? Novices aiming to enter the data science field. Sector professionals integrating data science into their expertise. Academicians and learners incorporating data science in academic pursuits. Business strategists utilizing data science for enhanced decision-making. Statisticians and analysts broadening their expertise into the data science domain. Career path Entry-Level Data Scientist: £25,000 - £40,000 Beginner Data Analyst: £22,000 - £35,000 Emerging Business Intelligence Specialist: £28,000 - £45,000 Data-Focused Research Scientist: £30,000 - £50,000 Novice Machine Learning Practitioner: £32,000 - £55,000 Data System Developer (Starter): £26,000 - £42,000 Prerequisites This Quick Data Science Approach from Scratch does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Quick Data Science Approach from Scratch was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01: Course Overview & Introduction to Data Science Introduction 00:02:00 Data Science Explanation 00:05:00 Need of Data Science 00:02:00 8 Common mistakes by Aspiring Data Scientists/Data Science Enthusiasts 00:08:00 Myths about Data Science 00:03:00 Section 02: Data Science Concepts Data Types and Variables 00:04:00 Descriptive Analysis 00:02:00 Data Cleaning 00:02:00 Feature Engineering 00:02:00 Data Thinking Development 00:03:00 Section 03: A Real Life Problem Problem Definition 00:05:00 Algorithms 00:14:00 Prediction 00:03:00 Learning Methods 00:05:00 Assignment Assignment - Quick Data Science Approach from Scratch 00:00:00

Isn't it interesting that you searched for something on the internet and some relevant results appeared? Alternatively, you can enter your daily data into a health app that automatically recommends a diet and exercise routine for you. All of this would not have been possible without data science. The modern world is entirely dependent on Machine Learning, Artificial Intelligence, Neural networks or data science in one phrase. Data science is a new field with no established leaders. It's too difficult to decide which one to learn, which leads to even more frustration because you can't make any progress. It is becoming more important, but the market for skilled data scientists is limited and competitive. What if you are one of those individuals? If you have a background in maths or statistics, we have good news: you can become a data scientist with little training! Anyone can become a data scientist with the help of our Data Science courses. Whatever your background, this training will teach you how to analyse and interpret data to generate new insights that lead to better decisions and results. Our interactive materials set us apart and make us more effective for our students. So don't be late to take your place. Enrol now! Learning Outcomes Understanding of the basic concepts and techniques in data science, such as data exploration, cleaning, and preprocessing Knowledge of statistical analysis methods, including hypothesis testing, regression analysis Learn probability theory and it's use in Data science Knowledge of Advanced regression & machine learning algorithms Ability to communicate data science results effectively to a non-technical audience. Key Highlights for Data Science Course: Developed by industry experts Instant e-certificate and hard copy dispatch by the next working day Interactive course with audio voice-over 24/7 Learning Assistance Lifetime access & update without any limits Unlimited Retake Exam and premium support for life Easy Accessibility to the Course Materials- Anytime, Anywhere - From Any Smart Device (Laptop, Tablet, Smartphone Etc.) 100% Learning satisfaction guarantee Covers to explore multiple job positions One-stop solution for entrepreneurs and Jobseekers Fastest growing sector Boost your salary on program completion Learn from diligent experts Expert-verified response for quality education So, You should not wait too long. Now is the time to enrol! Learn at your own pace from the comfort of your home, as the rich learning materials of this course are accessible from any place at any time. The curriculums are divided into tiny bite-sized modules by industry specialists. And you will get answers to all your queries from our experts. So, enrol and excel in your career with Compliance Central. Curriculum Breakdown of the Course Section 01: Let's get started Section 02: Descriptive statistics Section 03: Distributions Section 04: Probability theory Section 05: Hypothesis testing Section 06: Regressions Section 07: Advanced regression & machine learning algorithms Section 08: ANOVA (Analysis of Variance) Section 09: Wrap up CPD 15 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this course. Requirements To enrol in this Data Science course, all you need is a basic understanding of the English Language and an internet connection. Career path After completing this course, you can explore trendy and in-demand jobs related to Data Science, such as- Data Analyst: £25,000 to £45,000 per year Data Scientist: £35,000 to £60,000 per year Business Intelligence (BI) Analyst: £30,000 to £50,000 per year Machine Learning Engineer: £40,000 to £70,000 per year Data Engineer: £35,000 to £60,000 per year Data Consultant: £45,000 to £75,000 per year Certificates CPD Accredited Hard Copy Certificate Hard copy certificate - Included CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: £3.99 each Outside of the UK: £9.99 each CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate