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This comprehensive course will help you learn how to use the power of Python to evaluate your deep learning-based recommender system data sets based on user ratings and choices with a practical approach to building a deep learning-based recommender system by adopting a retrieval-based approach based on a two-tower model.

Learning Outcomes After completing this course, learners will be able to: Learn Python for data analysis using NumPy and Pandas Acquire a clear understanding of data visualisation using Matplotlib, Seaborn and Pandas Deepen your knowledge of Python for interactive and geographical potting using Plotly and Cufflinks Understand Python for data science and machine learning Get acquainted with Recommender Systems with Python Enhance your understanding of Python for Natural Language Processing (NLP) Description Whether you are from an engineering background or not you still can efficiently work in the field of data science and the machine learning sector, if you have proficient knowledge of Python. Since Python is the easiest and most used programming language, you can start learning this language now to advance your career with the Data Science And Machine Learning Using Python : A Bootcamp course. This course will give you a thorough understanding of the Python programming language. Moreover, it will show how can you use Python for data analysis and machine learning. Alongside that, from this course, you will get to learn data visualisation, and interactive and geographical plotting by using Python. The course will also provide detailed information on Python for data analysis, Natural Language Processing (NLP) and much more. Upon successful completion of this course, get a CPD- certificate of achievement which will enhance your resume and career. Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment After completing this course, you will be provided with some assessment questions. To pass that assessment, you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly. Career Path After completing this course, you can explore various career options such as Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst In the UK professionals usually get a salary of £25,000 - £30,000 per annum for these positions. Course Content 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 Machine Learning using Python : A Bootcamp 00:00:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

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Our dedicated team will work tirelessly to support your entire job searching process. From crafting a standout resume to submitting it to top companies, we'll ensure you have a compelling application that gets noticed. Expertly Crafted CV: Your resume is your ticket to the interview room. Our professional resume writers will create a customised CV highlighting your unique skills and experiences. This will maximise your chances of standing out among the competition. Strategic Placement: We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. One-On-One Consultation Sessions with Industry Experts: Gain invaluable insights and guidance from seasoned professionals who have thrived in the data analysis field. 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Here are the 25 courses we will provide once you enrol in the program: Course 01: Data Analysis Course 02: Data Science & Machine Learning with R Course 03: Data Analytics with Tableau Course 04: SQL Programming Course 05: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines Course 06: Data Analytics Course 07: Python Data Science with Numpy, Pandas and Matplotlib Course 08: Google Analytics Course 09: Business Intelligence and Data Mining Course 10: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query Course 11: JavaScript Functions Course 12: Data Protection and Data Security (GDPR) Training Certification Course 13: GDPR Training Course 14: Diploma in Python Programming Course 15: Data Center Training Essentials: General Introduction Course 16: Quick Data Science Approach from Scratch Course 17: Diploma in Statistics & Probability for Data Science & Machine Learning Course 18: Master JavaScript with Data Visualization Course 19: Data Analysis and Forecasting in Excel Course 20: AWS Certified Solutions Architect Associate Preparation Course 21: Statistical Analysis Course Course 22: SQL for Data Science, Data Analytics and Data Visualization Course 23: Learn MySQL from Scratch for Data Science and Analytics Course 24: Data Analysis & Forecasting Course 25: Data Structure These courses will help you to develop your knowledge and skills to become a successful data analyst. The Program is completed in 5 easy steps: Step 1 - Enrol in the program and start learning from the courses we provide After you enrol in the Data Analyst Program, you will get lifetime access to 25 premium courses related to data analysis. These courses will teach you the knowledge and skills required to become a successful data analyst. Our customer service team will help you and keep in contact with you every step of the way. Step 2 - Complete your courses and get certifications After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks for the first course and 80% for the rest relevant courses. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject. Step 3 - Get a consultation session from a professional data analyst Take your data analysis skills to new heights with a one-on-one consultation session led by a seasoned professional. Gain invaluable insights, expert tips, and tailored advice that will propel your career forward. Step 4 - Complete the CV and attend the interview Once you've successfully obtained the certifications, our team of professionals will build you a compelling CV and LinkedIn profile. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. Kickstart your IT career with a starting salary ranging from •25,000 to •40,000 annually. Step into the IT industry with the assurance of a promising future. Step 5 - We will not leave you until you get a job Our commitment to your success goes above and beyond. We won't stop until you land that dream job. With personalised support, expert guidance, and unwavering dedication, we'll be by your side until you secure the perfect opportunity. Your job search becomes our mission, ensuring you have the best chance at a successful career in data analysis. Don't let your dream career as a data analyst remain out of reach. You just have to learn and gain knowledge and skills. Finding a job is our task! We will remove most of your worries and help you focus on only developing your skills. So join our Data Analyst Program today, and let us be your trusted partner on your journey to success. CPD 100 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Data Analyst Program is ideal for: Aspiring data analysts eager to launch a successful career in the field. Recent graduates seeking practical skills and industry insights to stand out in a competitive job market. Professionals looking to transition into the dynamic world of data analysis and capitalise on emerging opportunities. Individuals with a passion for numbers, problem-solving, and uncovering meaningful insights from complex datasets. Job seekers seeking comprehensive support and guidance throughout the entire job searching and job finding process. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Requirements No experience required. Just enrol & start learning. Career path Our Data Analyst Program equips you with the skills to excel in data analysis roles. You'll thrive as a data analyst, data scientist, business analyst, or market research analyst, unlocking opportunities in diverse industries such as finance, healthcare, e-commerce, and technology. Act now, and let us guide you towards a brighter future. Enrol today! Certificates CPD Accredited e-Certificate Digital certificate - Included CPD Accredited Framed (Hardcopy) Certificate Hard copy certificate - Included Enrolment Letter Digital certificate - Included Student ID Card Digital certificate - Included The Quality Licence Scheme Endorsed Certificate of Achievement Hard copy certificate - Included

14 in 1 "IT and Analytics" Bundle only at £100 Get Hard Copy + PDF Certificates + Transcript + Student ID Card + e-Learning App as a Gift - Enrol Now Tired of browsing and searching for a IT and Analytics course you are looking for? Can't find the complete IT and Analytics package that fulfils all your needs? Then don't worry as you have just found the solution. Take a minute and look through this 14-in-1 extensive bundle that has everything you need to succeed in IT and Analytics and other relevant fields! After surveying thousands of learners just like you and considering their valuable feedback, this all-in-one bundle has been designed by industry experts. We prioritised what learners were looking for in a complete package and developed this in-demand course that will enhance your skills and prepare you for the competitive job market. Furthermore, to help you showcase your expertise in IT and Analytics, we have prepared a special gift of 1 hardcopy certificate and 1 PDF certificate for the title course completely free of cost. These certificates will enhance your credibility and encourage possible employers to pick you over the rest. This Bundle Consists of the following Premium courses: Course 01: Introduction to Data Analysis Course 02: Quick Data Science Approach from Scratch Course 03: Excel Pivot Tables Course 04: Google Data Studio: Data Analytics Course 05: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines Course 06: Business Intelligence and Data Mining Masterclass Course 07: Statistics & Probability for Data Science & Machine Learning Course 08: RCA: Root Cause Analysis Course 09: Master JavaScript with Data Visualization Course 10: CompTIA CySA+ Cybersecurity Analyst (CS0-002) Course 11: Electronic Document Management System Step Course 12: Information Management Course 13: Encryption Course 14: IT For Recruiters Enrol now to advance your career, and use the premium study materials from Apex Learning. Benefits you'll get from choosing Apex Learning for this training: Pay once and get lifetime access to 14 CPD courses Free e-Learning App for engaging reading materials & helpful assistance Certificates, student ID included in a one-time fee Free up your time - don't waste time and money travelling for classes Accessible, informative modules designed by expert instructors Learn anytime, from anywhere Study from your computer, tablet or mobile device CPD accredited course - improve the chance of gaining professional skills Curriculum Course 01: Introduction to Data Analysis Introduction Agenda and Principles of Process Management The Voice of the Process Working as One Team for Improvement Exercise: The Voice of the Customer Tools for Data Analysis The Pareto Chart The Histogram The Run Chart Exercise: Presenting Performance Data Understanding Variation The Control Chart Control Chart Example Control Chart Special Cases Interpreting the Control Chart Control Chart Exercise Strategies to Deal with Variation Using Data to Drive Improvement A Structure for Performance Measurement Data Analysis Exercise Course Project Test your Understanding ---------- Other Courses Are ---------- Course 02: Quick Data Science Approach from Scratch Course 03: Excel Pivot Tables Course 04: Google Data Studio: Data Analytics Course 05: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines Course 06: Business Intelligence and Data Mining Masterclass Course 07: Statistics & Probability for Data Science & Machine Learning Course 08: RCA: Root Cause Analysis Course 09: Master JavaScript with Data Visualization Course 10: CompTIA CySA+ Cybersecurity Analyst (CS0-002) Course 11: Electronic Document Management System Step Course 12: Information Management Course 13: Encryption Course 14: IT For Recruiters CPD 150 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this IT and Analytics bundle. Requirements This course is fully compatible with PCs, Macs, laptops, tablets and Smartphone devices. There is no time limit for completing this course; it can be studied in your own time at your own pace. Career path Having this expertise will increase the value of your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included You will get the PDF Certificate for the title course (Introduction to Data Analysis) absolutely Free! Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Introduction to Data Analysis) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

Are you someone wishing to learn the skills to analyze data professionally using Power BI? Do you want to learn to create impressive reports? Then this is the right course for you! Learn the complete workflow in Power BI from A-to-Z and advanced analytics with DAX-calculated columns and measures, forecasting, and advanced analytics.

This compact crash course teaches learners to optimize their Microsoft Power BI use, gain insights into circular dependency errors and the new DAX functions, and use Power BI template files to enhance data modeling/analysis. The course provides guidance and real-world examples to streamline Power BI projects and achieve data visualization goals effectively.

Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently

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This Bundle Consists of the following Premium courses: Course 01: Introduction to Data Analysis Course 02: Quick Data Science Approach from Scratch Course 03: Excel Pivot Tables Course 04: Google Data Studio: Data Analytics Course 05: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines Course 06: Business Intelligence and Data Mining Masterclass Course 07: Statistics & Probability for Data Science & Machine Learning Course 08: RCA: Root Cause Analysis Course 09: Master JavaScript with Data Visualization Course 10: CompTIA CySA+ Cybersecurity Analyst (CS0-002) Course 11: Electronic Document Management System Step Course 12: IT For Recruiters Enrol now to advance your career, and use the premium study materials from Apex Learning. 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PDF Certificate: Free (For The Title Course) Hard Copy Certificate: Free (For The Title Course) Curriculum Course 01: Introduction to Data Analysis Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding --------Other Courses Are-------- Course 02: Quick Data Science Approach from Scratch Course 03: Excel Pivot Tables Course 04: Google Data Studio: Data Analytics Course 05: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines Course 06: Business Intelligence and Data Mining Masterclass Course 07: Statistics & Probability for Data Science & Machine Learning Course 08: RCA: Root Cause Analysis Course 09: Master JavaScript with Data Visualization Course 10: CompTIA CySA+ Cybersecurity Analyst (CS0-002) Course 11: Electronic Document Management System Step Course 12: IT For Recruiters CPD 130 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this IT and Analytics Training bundle including- Students Graduates Job Seekers Job Holders Requirements Our Training is fully compatible with PCs, Macs, laptops, tablets and Smartphone devices. This Training course has been designed to be fully compatible with tablets and smartphones, so you can access your course on Wi-Fi, 3G or 4G. Career path Having this Training expertise will increase the value of your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included You will get the PDF Certificate for the title course (Introduction to Data Analysis) absolutely Free! Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Introduction to Data Analysis) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

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Gain knowledge in the programming languages commonly used in data analysis, such as Python and R. Become proficient in data visualisation and presentation. Develop an understanding of machine learning algorithms and their application in data analysis. Learn how to use various data analysis software, including Tableau and Google Analytics. The Data Analysis with Data Science & Machine Learning bundle includes a variety of courses aimed at providing theoretical knowledge in the field of data analysis. The bundle covers a wide range of topics, starting with the basics of data analysis such as data cleaning, exploration, and visualisation. With courses such as Introduction to Data Analysis, Data Analytics with Tableau, Complete Google Analytics Course, Python for Data Analysis, Quick Data Science Approach from Scratch, R Programming for Data Science, Learn MySQL from Scratch for Data Science and Analytics, and Master JavaScript with Data Visualization, learners can get a comprehensive understanding of data analysis concepts. The course material is presented in a theoretical format to help learners gain a deep understanding of the topics. Learners can engage with the material at their own pace. The course content is presented in a way that is easy to understand, making it ideal for those who are new to the field of data analysis. Course Curriculum: Data Analysis with Data Science & Machine Learning Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding CPD 140 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Professionals seeking to upskill and enhance their data analysis knowledge and abilities. Individuals interested in pursuing a career in data analysis, data science or machine learning. Business owners or entrepreneurs looking to gain insights into their data and make data-driven decisions. Students or recent graduates seeking to gain valuable experience and knowledge in data analysis. Anyone looking to expand their knowledge and understanding of data analysis and its useful applications. Requirements This Data Analysis with Data Science & Machine Learning course has been designed to be fully compatible with tablets and smartphones. Career path Data Analyst: £24k-£42k per annum. Business Intelligence Analyst: £25k-£60k per annum. Data Scientist: £27k-£65k per annum. Machine Learning Engineer: £28k-£80k per annum. Business Analyst: £24k-£52k per annum. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - £10 You will get the Hard Copy certificate for the Data Analysis with Data Science & Machine Learning course absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.