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Catering to the demands of busy professionals, our virtual training programs are as effective as face-to-face learning. For more queries, reach out to us: info@mangates.com

Catering to the demands of busy professionals, our virtual training programs are as effective as face-to-face learning. For more queries, reach out to us: info@mangates.com

Catering to the demands of busy professionals, our virtual training programs are as effective as face-to-face learning. For more queries, reach out to us: info@mangates.com

Catering to the demands of busy professionals, our virtual training programs are as effective as face-to-face learning. For more queries, reach out to us: info@mangates.com

Catering to the demands of busy professionals, our virtual training programs are as effective as face-to-face learning. For more queries, reach out to us: info@mangates.com

Negotiation Skills: Negotiation Skills Course Online Unlock the Power of Negotiation Skills: Negotiation Skills Course: Enrol Now! Unlock the power of effective negotiation skills with our dynamic Negotiation Skills course! Learn proven negotiation skills techniques and strategies from industry experts. Master the art of persuasion, communication, and collaboration through hands-on negotiation skills exercises. Elevate your career with unparalleled negotiation skills expertise. Enroll now for success! Courses you will get with Negotiation Skills: Negotiation Skills Course: Main Course: Level 5 Negotiation Skills Course Free Courses included with Negotiation Skills: Negotiation Skills Course Course 01: Residential Letting Course 02: Property Management Course 03: Property Development Course 04: Dealing with Difficult People [ Note: Free PDF certificate as soon as completing the Negotiation Skills: Negotiation Skills Course] Negotiation Skills: Negotiation Skills Course Online This Negotiation Skills: Negotiation Skills Course consists of 12 modules. Assessment Method of Negotiation Skills: Negotiation Skills Course After completing Negotiation Skills: Negotiation Skills Course, you will get quizzes to assess your learning. You will do the later modules upon getting 60% marks on the quiz test. Certification of Negotiation Skills: Negotiation Skills Course After completing the Negotiation Skills: Negotiation Skills Course, you can instantly download your certificate for FREE. Who is this course for? Negotiation Skills: Negotiation Skills Course Online This Negotiation Skills: Negotiation Skills Course is ideal for candidates committed to their ongoing professional development. Requirements Negotiation Skills: Negotiation Skills Course Online To enrol in this Negotiation Skills: Negotiation Skills Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Negotiation Skills: Negotiation Skills Course. Be energetic and self-motivated to complete our Negotiation Skills: Negotiation Skills Course. Basic computer Skill is required to complete our Negotiation Skills: Negotiation Skills Course. If you want to enrol in our Negotiation Skills: Negotiation Skills Course, you must be at least 15 years old. Career path Negotiation Skills: Negotiation Skills Course Online This Negotiation Skills: Negotiation Skills Course could hold the key to the leadership career of your dreams. Typical job titles in management and leadership include: Team Leader Manager Controller

Before you can effective lead others, you must first lead yourself. This 12 module program will help you develop in the following areas: Self Knowledge & Emotional Intelligence Identifying your strengths and building on them Values and Personal Mission Statement Self-motivation and personal goals Taking personal responsibility Discovering your purpose Authentic leadership and influencing others

Overview In the era where information is abundant and decisions are driven by data, have you ever pondered, 'what is machine learning?' or 'what is data science?' Dive into the realm of 'Data Science & Machine Learning with R from A-Z,' a comprehensive guide to unravel these complexities. This course effortlessly blends the foundational aspects of data science with the intricate depths of machine learning algorithms, all through the versatile medium of R. As the digital economy booms, the demand for machine learning jobs continues to surge. Equip yourself with the proficiency to navigate this dynamic field and transition from being an inquisitive mind to a sought-after professional in the space of data science and machine learning with R. Learning Outcomes: Understand the foundational concepts of data science and machine learning. Familiarise oneself with the R environment and its functionalities. Master data types, structures, and advanced techniques in R. Acquire proficiency in data manipulation and visual representation using R. Generate comprehensive reports using R Markdown and design web applications with R Shiny. Gain a thorough understanding of machine learning methodologies and their applications. Gain insights into initiating a successful career in the data science sector. Why buy this Data Science & Machine Learning with R from A-Z course? 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 Data Science & Machine Learning with R from A-Z 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 Data Science & Machine Learning with R from A-Z course for? This course is ideal for Individuals keen on exploring the intricacies of machine learning and data science. Aspiring data analysts and scientists looking to specialise in Machine Learning with R. IT professionals aiming to diversify their skill set in the emerging data-driven market. Researchers seeking to harness the power of R for data representation and analysis. Academics and students aiming to bolster their understanding of modern data practices with R. Prerequisites This Data Science & Machine Learning with R from A-Z does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Data Science & Machine Learning with R from A-Z 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 Data Scientist - Average salary range: £35,000 - £70,000 Per Annum Machine Learning Engineer - Average salary range: £50,000 - £80,000 Per Annum Data Analyst - Average salary range: £28,000 - £55,000 Per Annum R Developer - Average salary range: £30,000 - £60,000 Per Annum R Shiny Web Developer - Average salary range: £32,000 - £65,000 Per Annum Machine Learning Researcher - Average salary range: £40,000 - £75,000 Per Annum Course Curriculum Data Science and Machine Learning Course Intro Data Science and Machine Learning Introduction 00:03:00 What is Data Science 00:10:00 Machine Learning Overview 00:05:00 Who is This Course for 00:03:00 Data Science and Machine Learning Marketplace 00:05:00 Data Science and Machine Learning Job Opportunities 00:03:00 Getting Started with R Getting Started 00:11:00 Basics 00:06:00 Files 00:11:00 RStudio 00:07:00 Tidyverse 00:05:00 Resources 00:04:00 Data Types and Structures in R Unit Introduction 00:30:00 Basic Type 00:09:00 Vector Part One 00:20:00 Vectors Part Two 00:25:00 Vectors - Missing Values 00:16:00 Vectors - Coercion 00:14:00 Vectors - Naming 00:10:00 Vectors - Misc 00:06:00 Creating Matrics 00:31:00 List 00:32:00 Introduction to Data Frames 00:19:00 Creating Data Frames 00:20:00 Data Frames: Helper Functions 00:31:00 Data Frames Tibbles 00:39:00 Intermediate R Intermediate Introduction 00:47:00 Relational Operations 00:11:00 Conditional Statements 00:11:00 Loops 00:08:00 Functions 00:14:00 Packages 00:11:00 Factors 00:28:00 Dates and Times 00:30:00 Functional Programming 00:37:00 Data Import or Export 00:22:00 Database 00:27:00 Data Manipulation in R Data Manipulation in R Introduction 00:36:00 Tidy Data 00:11:00 The Pipe Operator 00:15:00 The Filter Verb 00:22:00 The Select Verb 00:46:00 The Mutate Verb 00:32:00 The Arrange Verb 00:10:00 The Summarize Verb 00:23:00 Data Pivoting 00:43:00 JSON Parsing 00:11:00 String Manipulation 00:33:00 Web Scraping 00:59:00 Data Visualization in R Data Visualization in R Section Intro 00:17:00 Getting Started 00:16:00 Aesthetics Mappings 00:25:00 Single Variable Plots 00:37:00 Two Variable Plots 00:21:00 Facets, Layering, and Coordinate Systems 00:18:00 Styling and Saving 00:12:00 Creating Reports with R Markdown Creating with R Markdown 00:29:00 Building Webapps with R Shiny Introduction to R Shiny 00:26:00 A Basic R Shiny App 00:31:00 Other Examples with R Shiny 00:34:00 Introduction to Machine Learning Machine Learning Part 1 00:22:00 Machine Learning Part 2 00:47:00 Starting A Career in Data Science Starting a Data Science Career Section Overview 00:03:00 Data Science Resume 00:04:00 Getting Started with Freelancing 00:05:00 Top Freelance Websites 00:05:00 Personal Branding 00:05:00 Importance of Website and Blo 00:04:00 Networking Do's and Don'ts 00:04:00 Assignment Assignment - Data Science & Machine Learning with R 00:00:00

Embark on a captivating journey into the realm of Python 3 Programming with our comprehensive course. From unraveling the mysteries of mathematical operators to mastering advanced topics like threading and socket terminology, this course is your gateway to the dynamic world of coding. Engage with hands-on sessions, explore the power of Python libraries, and conquer the art of class implementation. Your digital odyssey begins with the basics and evolves into a sophisticated understanding of programming essentials. Our creatively crafted curriculum promises an exhilarating learning experience, making coding accessible to enthusiasts and novices alike. Learning Outcomes Master the fundamentals of Python 3, from basic math operations to complex string manipulations. Develop practical skills in working with lists, dictionaries, and advanced string manipulation techniques. Gain proficiency in file handling, regex, and navigating systems using the OS library. Understand the principles of classes, inheritance, and the manipulation of date and time. Explore advanced topics such as performing HTTP requests, socket programming, and sending emails using SMTPlib. Why choose this Python 3 Programming 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 Python 3 Programming course for? Individuals eager to start their coding journey without prior programming experience. Students seeking a comprehensive understanding of Python 3 programming. Professionals looking to enhance their skills and stay relevant in the evolving tech landscape. Coding enthusiasts excited to explore the vast possibilities Python 3 offers. Anyone desiring a hands-on and engaging learning experience in programming. Career path Python Developer: £35,000 - £55,000 Data Analyst: £30,000 - £50,000 Software Engineer: £40,000 - £65,000 Machine Learning Engineer: £45,000 - £70,000 Web Developer: £32,000 - £50,000 Network Programmer: £38,000 - £60,000 Prerequisites This Python 3 Programming does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python 3 Programming 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 Welcome to Python 3 course! 00:03:00 Why you should learn Python 3 00:04:00 Installing Python 3 on Windows 00:08:00 Installing Python3 on Ubuntu and Mac 00:08:00 Taking a closer look at Python 3 IDLE 00:05:00 Section 02 Math operators 00:12:00 Strings 00:08:00 Variables and variable naming rules 00:11:00 Our first program! 00:12:00 Type, Len, Str, Int, Float , functions 00:09:00 True or false Boolean 00:10:00 IF statement 00:05:00 IF & ELSE 00:13:00 Using ELIF for multiple statements 00:09:00 While loop 00:16:00 Using Continue in a loop 00:06:00 FOR loop 00:10:00 Importing Python libraries 00:12:00 Section 03 Defining functions in Python 3 00:15:00 Local and global variables 00:10:00 Coding guess the number program 00:16:00 Reverse a string function 00:07:00 Calculate area of a circle program 00:11:00 Simple Python calculator 00:15:00 Removing vowels from string program 00:13:00 Find the largest number out of three 00:16:00 Section 04 Python 3 lists 00:15:00 Creating smaller out of bigger list 00:09:00 Manipulating lists and elements 00:08:00 Append, insert, remove, sort 00:11:00 Tuples 00:13:00 Introduction to dictionaries 00:11:00 Values, keys, items, get 00:08:00 Dictionary comprehension - part 1 00:08:00 Dictionary comprehension - part 2 00:07:00 Advance string manipulation 00:12:00 Upper(), lower(), isupper(), islower() 00:09:00 Split, strip, join, startswith, endswith 00:13:00 Section 05 Navigating through system with OS library 00:29:00 Reading and writing to files 00:16:00 Reversing text from a file 00:17:00 Section 06 Try and except 00:13:00 Section 07 Classes 00:22:00 Changing class attributes 00:10:00 Built in class attributes 00:08:00 Using your class in a different program 00:05:00 Using your class in a program 00:26:00 Implementing students count option 00:05:00 Class inheritance 00:12:00 Overriding methods in a class 00:08:00 Section 08 Printing and calculating date and time 00:30:00 Different date formats 00:09:00 Section 09 Extracting useful data 00:23:00 Regex - part 1 00:23:00 Regex - part 2 00:17:00 Section 10 Performing HTTP GET request 00:20:00 Performing post request 00:04:00 Handling website redirections 00:03:00 BeautifulSoup 00:29:00 Encoding in requests 00:12:00 Session and cookies 00:21:00 SSL certificate, authentication 00:21:00 Json library and proxies 00:10:00 Section 11 Socket terminology 00:09:00 Connecting two machines 00:21:00 Coding a chat program 00:35:00 Receiving Desired Amount of Data 00:20:00 Socket Timeout and Options 00:08:00 UDP Server & Client 00:13:00 AF_UNIX & Raw sockets 00:14:00 Section 12 Theory Behind Threaded Server 00:15:00 Thread & Threading 00:50:00 Section 13 Sending Emails Using SMTPlib 00:32:00 PDF Files 00:11:00 Images In Python 00:16:00 Assignment Assignment - Python 3 Programming 00:00:00

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.