763 Researcher courses in Lymm delivered Online

Do you want to master the essential mathematical skills for data science and machine learning? Do you want to learn how to apply statistics and probability to real-world problems and scenarios? If yes, then this course is for you! In this course, you will learn the advanced concepts and techniques of statistics and probability that are widely used in data science and machine learning. You will learn how to describe and analyse data using descriptive statistics, distributions, and probability theory. You will also learn how to perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data. You will gain hands-on experience with practical exercises and projects using Python and R. Learning Outcomes By the end of this course, you will be able to: Apply descriptive statistics, distributions, and probability theory to summarise and visualise data Perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data Use Python and R to implement statistical and machine learning methods Interpret and communicate the results of your analysis using appropriate metrics and visualisations Solve real-world problems and scenarios using statistics and probability Why choose this Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 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 Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 course for? This course is for anyone who wants to learn the advanced concepts and techniques of statistics and probability for data science and machine learning. This course is suitable for: Data scientists, machine learning engineers, and analysts who want to enhance their skills and knowledge Students and researchers who want to learn the mathematical foundations of data science and machine learning Professionals and managers who want to understand and apply data-driven decision making Hobbyists and enthusiasts who want to explore and learn from data Anyone who loves statistics and probability and wants to challenge themselves Career path Data Scientist (£35,000 - £55,000) Machine Learning Engineer (£40,000 - £60,000) Statistician (£35,000 - £55,000) Data Analyst (£40,000 - £60,000) Business Intelligence Analyst (£45,000 - £65,000) Senior Data Analyst (£50,000 - £70,000) Prerequisites This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 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. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Section 01: Let's get started Welcome! 00:02:00 What will you learn in this course? 00:06:00 How can you get the most out of it? 00:06:00 Section 02: Descriptive statistics Intro 00:03:00 Mean 00:06:00 Median 00:05:00 Mode 00:04:00 Mean or Median? 00:08:00 Skewness 00:08:00 Practice: Skewness 00:01:00 Solution: Skewness 00:03:00 Range & IQR 00:10:00 Sample vs. Population 00:05:00 Variance & Standard deviation 00:11:00 Impact of Scaling & Shifting 00:19:00 Statistical moments 00:06:00 Section 03: Distributions What is a distribution? 00:10:00 Normal distribution 00:09:00 Z-Scores 00:13:00 Practice: Normal distribution 00:04:00 Solution: Normal distribution 00:07:00 Section 04: Probability theory Intro 00:01:00 Probability Basics 00:10:00 Calculating simple Probabilities 00:05:00 Practice: Simple Probabilities 00:01:00 Quick solution: Simple Probabilities 00:01:00 Detailed solution: Simple Probabilities 00:06:00 Rule of addition 00:13:00 Practice: Rule of addition 00:02:00 Quick solution: Rule of addition 00:01:00 Detailed solution: Rule of addition 00:07:00 Rule of multiplication 00:11:00 Practice: Rule of multiplication 00:01:00 Solution: Rule of multiplication 00:03:00 Bayes Theorem 00:10:00 Bayes Theorem - Practical example 00:07:00 Expected value 00:11:00 Practice: Expected value 00:01:00 Solution: Expected value 00:03:00 Law of Large Numbers 00:08:00 Central Limit Theorem - Theory 00:10:00 Central Limit Theorem - Intuition 00:08:00 Central Limit Theorem - Challenge 00:11:00 Central Limit Theorem - Exercise 00:02:00 Central Limit Theorem - Solution 00:14:00 Binomial distribution 00:16:00 Poisson distribution 00:17:00 Real life problems 00:15:00 Section 05: Hypothesis testing Intro 00:01:00 What is a hypothesis? 00:19:00 Significance level and p-value 00:06:00 Type I and Type II errors 00:05:00 Confidence intervals and margin of error 00:15:00 Excursion: Calculating sample size & power 00:11:00 Performing the hypothesis test 00:20:00 Practice: Hypothesis test 00:01:00 Solution: Hypothesis test 00:06:00 T-test and t-distribution 00:13:00 Proportion testing 00:10:00 Important p-z pairs 00:08:00 Section 06: Regressions Intro 00:02:00 Linear Regression 00:11:00 Correlation coefficient 00:10:00 Practice: Correlation 00:02:00 Solution: Correlation 00:08:00 Practice: Linear Regression 00:01:00 Solution: Linear Regression 00:07:00 Residual, MSE & MAE 00:08:00 Practice: MSE & MAE 00:01:00 Solution: MSE & MAE 00:03:00 Coefficient of determination 00:12:00 Root Mean Square Error 00:06:00 Practice: RMSE 00:01:00 Solution: RMSE 00:02:00 Section 07: Advanced regression & machine learning algorithms Multiple Linear Regression 00:16:00 Overfitting 00:05:00 Polynomial Regression 00:13:00 Logistic Regression 00:09:00 Decision Trees 00:21:00 Regression Trees 00:14:00 Random Forests 00:13:00 Dealing with missing data 00:10:00 Section 08: ANOVA (Analysis of Variance) ANOVA - Basics & Assumptions 00:06:00 One-way ANOVA 00:12:00 F-Distribution 00:10:00 Two-way ANOVA - Sum of Squares 00:16:00 Two-way ANOVA - F-ratio & conclusions 00:11:00 Section 09: Wrap up Wrap up 00:01:00 Assignment Assignment - Statistics & Probability for Data Science & Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science 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 R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science 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 Unit 01: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's next? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00 Assignment Assignment - R Programming for Data Science 00:00:00

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up 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 Essentials 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 Python for Data Analysis using NumPy 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 Python for Data Analysis using Pandas 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 Python for Data Visualization using matplotlib 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 Python for Data Visualization using Seaborn 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 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks 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 Capstone Project - Python for Data Analysis & Visualization 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 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model 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 Python for Machine Learning - scikit-learn - Logistic Regression Model 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 Python for Machine Learning - scikit-learn - K Nearest Neighbors 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 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests 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 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) 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 Python for Machine Learning - scikit-learn - K Means Clustering 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 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) 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 Recommender Systems with Python - (Additional Topic) 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 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) 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 Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Mastering Psychology Online Training Psychology is an enthralling subject that leads to many career opportunities. You could specialize in a field such as Neuropsychology or Child Psychology if you desire. If you want to work on a freelance basis, you could specialize in Clinical Psychology or Counselling. You could even specialize in Forensic or Criminal Psychology to help in reducing crime. As you can see, there are numerous options available with a Master of Psychology, and you could enjoy a well-paid and fulfilling career once you have qualified. This Mastering Psychology course introduces various essential concepts, including fundamentals of Psychology, the biological behavior of Psychology, Psychology of Consciousness, Introduction to Intelligence, Psychological Disorders, Developmental Psychology, Social Psychology, and much more. Few professional positions demand greater commitment and responsibility than a qualified psychologist. Nevertheless, those who have what it takes to succeed in psychology enjoy a uniquely rewarding career with limitless opportunities for advancement. If a career dedicated to the well-being of others appeals to you, this Mastering Psychology comes highly recommended! Let's see what those 4 courses are included in this Bundle Courses Course 01: Mastering Psychology Course 02: Clinical Psychology Diploma Course 03: Level 3 Diploma in Healthcare Support Course 04: Level 2 Award in Support Work in Schools and Colleges Other Benefits of This Bundle Courses Free 4 PDF Certificate Lifetime Access Free Retake Exam Tutor Support [ Note: Free PDF certificate as soon as completing the Mastering Psychology course] Mastering Psychology Training Industry Experts Designed this Mastering Psychology course into 16 detailed modules. ---------------- Assessment Method of Mastering Psychology After completing each module of the Diploma in Mastering Psychology Course, you will find automated MCQ quizzes. To unlock the next module, you need to complete the quiz task and get at least 60% marks. Certification of Mastering Psychology After completing the MCQ/Assignment assessment for this Diploma in Mastering Psychology course, you will be entitled to a Certificate of Completion from Training Tale. Who is this course for? Mastering Psychology Online Training This course is suitable for: Advice Workers Careers Advisers Counsellors Human Resources Officers Market Researchers Play Therapists Psychotherapists Requirements Mastering Psychology Online Training There are no specific requirements for this Mastering Psychology course because it does not require any advanced knowledge or skills. Certificates Certificate of completion Digital certificate - Included

Unlock the science behind drug interactions and therapeutic principles with our comprehensive "Principles of Pharmacology" course. Perfect for aspiring pharmacologists, healthcare professionals, and students, this course delves into essential topics essential for understanding the impact of medications on the human body. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access In the "Principles of Pharmacology" course, learners will explore essential concepts and practices in the study of how drugs affect the body. They will gain a deep understanding of how medications are developed, regulated, and used in treating various health conditions. The course covers the effects of drugs on the nervous system, heart, hormones, and immune responses, providing insights into their mechanisms and applications. Students will also learn about the specific pharmacological treatments for cancer and understand the principles of toxicology, including how substances can be harmful to biological systems. This comprehensive curriculum equips learners with crucial knowledge to understand drug actions, their therapeutic uses, and potential risks, preparing them to contribute effectively in fields related to healthcare, research, and pharmaceutical industries. Course Curriculum Module 01: Fundamental Principles of Pharmacology Module 02: Drug Development and Regulation Module 03: Neuropharmacology Module 04: Cardiovascular Pharmacology Module 05: Endocrine Pharmacology Module 06: Inflammation and Immune Pharmacology Module 07: Chemotherapy Module 08: Toxicology Learning Outcomes: Understand fundamental principles of pharmacology and their applications in healthcare. Analyze the process of drug development and the regulatory framework. Explain neuropharmacology and its implications in neurological disorders treatment. Evaluate cardiovascular pharmacology and its impact on heart health management. Discuss endocrine pharmacology and its role in hormonal balance maintenance. Explore inflammation and immune pharmacology in the context of immune system regulation. CPD 10 CPD hours / points Accredited by CPD Quality Standards Principles of Pharmacology 1:33:31 1: Module 01: Fundamental Principles of Pharmacology 13:50 2: Module 02: Drug Development and Regulation 09:27 3: Module 03: Neuropharmacology 09:35 4: Module 04: Cardiovascular Pharmacology 12:25 5: Module 05: Endocrine Pharmacology 14:46 6: Module 06: Inflammation and Immune Pharmacology 09:27 7: Module 07: Chemotherapy 11:50 8: Module 08: Toxicology 11:11 9: CPD Certificate - Free 01:00 Who is this course for? Pharmacology students seeking foundational knowledge. Healthcare professionals expanding their understanding of pharmacological principles. Researchers focusing on drug development and regulatory aspects. Medical professionals specializing in neurological or cardiovascular fields. Biomedical scientists interested in pharmacological research. Career path Pharmacologist Pharmaceutical Research Scientist Clinical Trial Coordinator Cardiovascular Pharmacologist Neuropharmacologist Toxicologist Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Dive into the fascinating world of genetics with our comprehensive online course, designed to equip you with essential knowledge and skills in genetic science. Whether you're a student, healthcare professional, or simply curious about how genes shape life, this course offers invaluable insights and practical applications. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access In the "Fundamentals of Genetics" course, learners delve into the core principles and applications of genetics. They begin by understanding foundational genetic concepts, exploring how genes work and their role in inheritance. Moving forward, learners explore genetics in the context of genomics, studying how entire genomes contribute to traits and diseases. They then examine genetic disorders, learning about various conditions caused by genetic mutations and their implications. The course highlights practical applications of genetic knowledge, showing learners how genetics is used in fields like medicine, agriculture, and forensics. Finally, learners delve into genetic counseling, understanding how professionals help individuals and families understand and cope with genetic conditions. Throughout the course, learners gain a comprehensive understanding of genetics, from basic principles to real-world applications, preparing them to grasp the impact of genetics on both scientific advancements and everyday life. Course Curriculum Module 01: Fundamental Genetic Concept Module 02: Genetics and Genomics Module 03: Genetic Disorders Module 04: Application of Genetics Knowledge Module 05: Genetic Counselling Learning Outcomes: Understand fundamental genetic concepts and their practical applications. Analyse the role of genetics and genomics in modern research. Identify various genetic disorders and their underlying genetic mechanisms. Apply genetic knowledge to real-world scenarios and case studies. Explain the principles and processes involved in genetic counselling. Evaluate ethical and social implications related to genetic information. CPD 10 CPD hours / points Accredited by CPD Quality Standards Fundamental of Genetics 36:29 1: Module 01: Fundamental Genetic Concept 05:34 2: Module 02: Genetics and Genomics 05:59 3: Module 03: Genetic Disorders 07:46 4: Module 04: Application of Genetics Knowledge 09:07 5: Module 05: Genetic Counselling 07:03 6: CPD Certificate - Free 01:00 Who is this course for? Students pursuing biology or related sciences degrees. Healthcare professionals seeking genetics knowledge enhancement. Researchers exploring genetic aspects in their field. Educators teaching genetics at secondary or tertiary levels. Individuals interested in genetic counselling careers. Career path Geneticist Research Scientist Clinical Geneticist Genetic Counsellor Biomedical Scientist Pharmaceutical Geneticist Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Unlock the gateway to understanding the intricate world of clinical psychology. Dive deep into modules that unravel the complexities of severe mental health problems, clinical assessment, and therapeutic models. Journey through the realms of interviewing, observation, and consultation, acquiring indispensable skills. Explore the delicate art of working with children and older individuals, gaining holistic insights. This course is your compass through the rich tapestry of clinical psychology. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access Embark on a transformative odyssey, honing skills that empower compassionate care. This curriculum, meticulously designed, is your key to unlocking the door to a fulfilling career in the field. Elevate your understanding and practical proficiency in clinical psychology, charting a course towards meaningful impact. Discover the art and science that underpin the nuances of psychological well-being. Enrich your professional journey with this comprehensive exploration of the theoretical foundations in clinical psychology. Course Curriculum Module 1: Mental Health Challenges Module 2: Assessment in Clinical Context Module 3: Techniques in Psychology Interviews and Observations Module 4: Professional Consultation Practices Module 5: Varied Approaches to Therapy Module 6: Child-Centric Practices in Psychology Module 7: Psychology with Elderly Individuals Learning Outcomes: Analyze and diagnose severe mental health problems for effective intervention strategies. Conduct precise clinical assessments for tailored treatment plans. Master the art of insightful interviewing and observation techniques. Collaborate through consultation, ensuring holistic client care. Explore diverse therapeutic models for comprehensive psychological support. Develop specialised skills for empathetic interaction with children and older individuals. CPD 10 CPD hours / points Accredited by CPD Quality Standards Clinical Psychology 1:35:54 1: Module 1: Mental Health Challenges 11:25 2: Module 2: Assessment in Clinical Context 15:38 3: Module 3: Techniques in Psychology Interviews and Observations 13:44 4: Module 4: Professional Consultation Practices 10:06 5: Module 5: Varied Approaches to Therapy 16:39 6: Module 6: Child-Centric Practices in Psychology 14:28 7: Module 7: Psychology with Elderly Individuals 13:54 Who is this course for? Aspiring Clinical Psychologists seeking advanced theoretical grounding. Mental Health Professionals aiming to deepen their expertise. Counsellors and Therapists aspiring to broaden their understanding. Social Workers desiring a comprehensive grasp of clinical psychology. Educators and Researchers interested in the psychological well-being domain. Career path Clinical Psychologist Counselling Psychologist Mental Health Specialist Psychiatric Social Worker Research Psychologist Educational Psychologist Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Unlock the science behind drug interactions and therapeutic principles with our comprehensive "Principles of Pharmacology" course. Perfect for aspiring pharmacologists, healthcare professionals, and students, this course delves into essential topics essential for understanding the impact of medications on the human body. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access In the "Principles of Pharmacology" course, learners will explore essential concepts and practices in the study of how drugs affect the body. They will gain a deep understanding of how medications are developed, regulated, and used in treating various health conditions. The course covers the effects of drugs on the nervous system, heart, hormones, and immune responses, providing insights into their mechanisms and applications. Students will also learn about the specific pharmacological treatments for cancer and understand the principles of toxicology, including how substances can be harmful to biological systems. This comprehensive curriculum equips learners with crucial knowledge to understand drug actions, their therapeutic uses, and potential risks, preparing them to contribute effectively in fields related to healthcare, research, and pharmaceutical industries. Course Curriculum Module 01: Fundamental Principles of Pharmacology Module 02: Drug Development and Regulation Module 03: Neuropharmacology Module 04: Cardiovascular Pharmacology Module 05: Endocrine Pharmacology Module 06: Inflammation and Immune Pharmacology Module 07: Chemotherapy Module 08: Toxicology Learning Outcomes: Understand fundamental principles of pharmacology and their applications in healthcare. Analyze the process of drug development and the regulatory framework. Explain neuropharmacology and its implications in neurological disorders treatment. Evaluate cardiovascular pharmacology and its impact on heart health management. Discuss endocrine pharmacology and its role in hormonal balance maintenance. Explore inflammation and immune pharmacology in the context of immune system regulation. CPD 10 CPD hours / points Accredited by CPD Quality Standards Principles of Pharmacology 1:33:31 1: Module 01: Fundamental Principles of Pharmacology 13:50 2: Module 02: Drug Development and Regulation 09:27 3: Module 03: Neuropharmacology 09:35 4: Module 04: Cardiovascular Pharmacology 12:25 5: Module 05: Endocrine Pharmacology 14:46 6: Module 06: Inflammation and Immune Pharmacology 09:27 7: Module 07: Chemotherapy 11:50 8: Module 08: Toxicology 11:11 9: CPD Certificate - Free 01:00 Who is this course for? Pharmacology students seeking foundational knowledge. Healthcare professionals expanding their understanding of pharmacological principles. Researchers focusing on drug development and regulatory aspects. Medical professionals specializing in neurological or cardiovascular fields. Biomedical scientists interested in pharmacological research. Career path Pharmacologist Pharmaceutical Research Scientist Clinical Trial Coordinator Cardiovascular Pharmacologist Neuropharmacologist Toxicologist Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Unlock the science behind drug interactions and therapeutic principles with our comprehensive "Principles of Pharmacology" course. Perfect for aspiring pharmacologists, healthcare professionals, and students, this course delves into essential topics essential for understanding the impact of medications on the human body. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access In the "Principles of Pharmacology" course, learners will explore essential concepts and practices in the study of how drugs affect the body. They will gain a deep understanding of how medications are developed, regulated, and used in treating various health conditions. The course covers the effects of drugs on the nervous system, heart, hormones, and immune responses, providing insights into their mechanisms and applications. Students will also learn about the specific pharmacological treatments for cancer and understand the principles of toxicology, including how substances can be harmful to biological systems. This comprehensive curriculum equips learners with crucial knowledge to understand drug actions, their therapeutic uses, and potential risks, preparing them to contribute effectively in fields related to healthcare, research, and pharmaceutical industries. Course Curriculum Module 01: Fundamental Principles of Pharmacology Module 02: Drug Development and Regulation Module 03: Neuropharmacology Module 04: Cardiovascular Pharmacology Module 05: Endocrine Pharmacology Module 06: Inflammation and Immune Pharmacology Module 07: Chemotherapy Module 08: Toxicology Learning Outcomes: Understand fundamental principles of pharmacology and their applications in healthcare. Analyze the process of drug development and the regulatory framework. Explain neuropharmacology and its implications in neurological disorders treatment. Evaluate cardiovascular pharmacology and its impact on heart health management. Discuss endocrine pharmacology and its role in hormonal balance maintenance. Explore inflammation and immune pharmacology in the context of immune system regulation. CPD 10 CPD hours / points Accredited by CPD Quality Standards Principles of Pharmacology 1:33:31 1: Module 01: Fundamental Principles of Pharmacology 13:50 2: Module 02: Drug Development and Regulation 09:27 3: Module 03: Neuropharmacology 09:35 4: Module 04: Cardiovascular Pharmacology 12:25 5: Module 05: Endocrine Pharmacology 14:46 6: Module 06: Inflammation and Immune Pharmacology 09:27 7: Module 07: Chemotherapy 11:50 8: Module 08: Toxicology 11:11 9: CPD Certificate - Free 01:00 Who is this course for? Pharmacology students seeking foundational knowledge. Healthcare professionals expanding their understanding of pharmacological principles. Researchers focusing on drug development and regulatory aspects. Medical professionals specializing in neurological or cardiovascular fields. Biomedical scientists interested in pharmacological research. Career path Pharmacologist Pharmaceutical Research Scientist Clinical Trial Coordinator Cardiovascular Pharmacologist Neuropharmacologist Toxicologist Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Unlock the fundamentals of Islamic finance with our comprehensive online course. Whether you're new to the field or seeking to deepen your understanding, this course offers a structured exploration into the principles that govern ethical financial practices in Islam. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access In this course on Fundamentals of Islamic Finance, learners delve into the ethical principles and operational framework of financial practices aligned with Islamic law (Shariah). They explore the fundamental concepts that distinguish Islamic finance from conventional finance, such as the prohibition of interest (riba) and the emphasis on profit-sharing arrangements (mudarabah and musharakah). The course covers practical applications of Islamic finance in various financial products and services, including Takaful (Islamic insurance) and Islamic funds. It also addresses risk management strategies unique to Islamic finance contexts. Learners gain insights into the adaptation and implementation of Islamic financial principles within the regulatory environment of the United Kingdom. Overall, the curriculum equips learners with a comprehensive understanding of how Islamic finance operates ethically and effectively within global financial systems, preparing them to navigate and contribute to this specialized field. Course Curriculum Module 01: Ethics and Principles of Islamic Finance Module 02: Fundamentals of Islamic Finance Module 03: Islamic Finance in Practice Module 04: Takaful Module 05: Islamic Funds and Risk Management Module 06: Islamic Finance in the UK Learning Outcomes: Explain key principles of Islamic finance ethics and regulations confidently. Apply fundamental concepts of Islamic finance in theoretical scenarios effectively. Analyse practical applications of Islamic finance principles in real-world contexts. Describe the principles and operations of Takaful insurance accurately. Evaluate risk management strategies within Islamic funds comprehensively. Discuss the development and challenges of Islamic finance in the UK. CPD 10 CPD hours / points Accredited by CPD Quality Standards Fundamentals of Islamic Finance 1:26:06 1: Module 01: Ethics and Principles of Islamic Finance 11:06 2: Module 02: Fundamentals of Islamic Finance 14:52 3: Module 03: Islamic Finance in Practice 10:22 4: Module 04: Takaful 14:03 5: Module 05: Islamic Funds and Risk Management 18:28 6: Module 06: Islamic Finance in the UK 16:15 7: CPD Certificate - Free 01:00 Who is this course for? Financial professionals seeking knowledge in Islamic finance principles. Students interested in understanding ethical financial practices in Islamic contexts. Researchers exploring the application of Sharia-compliant finance in global markets. Individuals pursuing careers in Islamic banking and finance sectors. Consultants advising on financial services compliant with Islamic law. Career path Islamic Finance Analyst Sharia Compliance Officer Takaful Insurance Specialist Islamic Investment Advisor Financial Risk Manager Islamic Finance Consultant Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.