486 Machine Learning (ML) courses

Duration 1 Days 6 CPD hours This course is intended for To gain the most from attending this course you should possess the following incoming skills: Basic knowledge of programming concepts and syntax in Python. Familiarity with common data formats such as CSV, JSON, and XML. Experience using command-line interfaces and basic text editing tools. Understanding of basic machine learning concepts and algorithms. Overview Working in an interactive learning environment, led by our engaging expert, you will: Gain a solid understanding of prompt engineering concepts and their applications in software development and AI-driven solutions. Master the techniques for preprocessing and cleaning text data to ensure high-quality inputs for AI models like GPT-4. Develop expertise in GPT-4 tokenization, input formatting, and controlling model behavior for various tasks and requirements. Acquire the ability to design, optimize, and test prompts effectively, catering to diverse business applications and use cases. Learn advanced prompt engineering techniques, such as conditional text generation and multi-turn conversations, to create more sophisticated AI solutions. Practice creating prompts to generate, run, and test code in a chosen programming language using GPT-4 and OpenAI Codex. Understand the ethical implications and best practices in responsible AI deployment, ensuring fair and unbiased AI applications in software development. Prompt Engineering offers coders and software developers a competitive edge by empowering them to develop more effective and efficient AI-driven solutions in their projects. By harnessing the capabilities of cutting-edge AI models like GPT-4, coders can automate repetitive tasks, enhance natural language understanding, and even generate code suggestions, boosting productivity and creativity. In addition, mastering prompt engineering can contribute to improved job security, as professionals with these in-demand skills are highly sought after in the rapidly evolving tech landscape. Quick Start to Prompt Engineering for Coders and Software Developers is a one day course designed to get you quickly up and running with the prompting skills required to out AI to work for you in your development efforts. Guided by our AI expert, you?ll explore key topics such as text preprocessing, data cleansing, GPT-4 tokenization, input formatting, prompt design, and optimization, as well as ethical considerations in prompt engineering. In the hands-on labs you?ll explore tasks such as formatting inputs for GPT-4, designing and optimizing prompts for business applications, and implementing multi-turn conversations with AI. You?ll work with innovative tools like the OpenAI API, OpenAI Codex, and OpenAI Playground, enhancing your learning experience while preparing you for integrating prompt engineering into your professional toolkit. By the end of this immersive course, you?ll have the skills necessary to effectively use prompt engineering in your software development projects. You'll be able to design, optimize, and test prompts for various business tasks, integrate GPT-4 with other software platforms, and address ethical concerns in AI deployment. INTRODUCTION TO PROMPT ENGINEERING * Overview of prompt engineering and its importance in AI applications * Major applications of prompt engineering in business * Common challenges faced in prompt engineering * Overview of GPT-4 and its role in prompt engineering * Key terminology and concepts in prompt engineering GETTING THINGS READY: TEXT PREPROCESSING AND DATA CLEANSING * Importance of data preprocessing in prompt engineering * Techniques for text cleaning and normalization * Tokenization and n-grams * Stop word removal and stemming * Regular expressions and pattern matching GPT-4 TOKENIZATION AND INPUT FORMATTING * GPT-4 tokenization and its role in prompt engineering * Understanding and formatting GPT-4 inputs * Context windows and token limits * Controlling response length and quality * Techniques for handling out-of-vocabulary tokens PROMPT DESIGN AND OPTIMIZATION * Master the skills to design, optimize, and test prompts for various business tasks. * Designing effective prompts for different tasks * Techniques for prompt optimization * GPT-4 system and user parameters for controlling behavior * Importance of prompt testing and iteration * Best practices for prompt engineering in business applications ADVANCED TECHNIQUES AND TOOLS IN PROMPT ENGINEERING * Learn advanced techniques and tools for prompt engineering and their integration in business applications. * Conditional text generation with GPT-4 * Techniques for handling multi-turn conversations * Overview of tools for prompt engineering: OpenAI API, OpenAI Codex, and OpenAI Playground * Integration of GPT-4 with other software platforms and tools * Monitoring and maintaining prompt performance CODE GENERATION AND TESTING WITH PROMPT ENGINEERING * Develop the skills to generate, integrate, and test AI-generated code effectively, enhancing productivity and creativity in software development projects. * Introduction to code generation with AI models like GPT-4 * Designing prompts for code generation across programming languages * Techniques for specifying requirements and constraints in prompts * Generating and interpreting code snippets using AI-driven solutions * Integrating generated code into existing projects and codebases * Best practices for testing and validating AI-generated code ETHICS AND RESPONSIBLE AI * Understand the ethical implications of prompt engineering and the importance of responsible AI deployment in business. * Ethical considerations in prompt engineering * Bias in AI systems and its impact on prompt engineering * Techniques to minimize bias and ensure fairness * Best practices for responsible AI deployment in business applications * Monitoring and addressing ethical concerns in prompt engineering

Duration 3 Days 18 CPD hours This course is intended for Attendee roles might include: Software Developers/Programmers Data Scientists Machine Learning Engineers AI Researchers User Interface (UI) and User Experience (UX) Designers Technical Product Managers Technical Team Leads Overview Working in an interactive learning environment, led by our engaging AI expert you'll: Develop a strong foundational understanding of generative AI techniques and their applications in software development. Gain hands-on experience working with popular generative AI models, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer models. Master the use of leading AI libraries and frameworks, such as TensorFlow, Keras, and Hugging Face Transformers, for implementing generative AI models. Acquire the skills to design, train, optimize, and evaluate custom generative AI models tailored to specific software development tasks. Learn to fine-tune pre-trained generative AI models for targeted applications and deploy them effectively in various environments, including cloud-based services and on-premises servers. Understand and address the ethical, legal, and safety considerations of using generative AI, including mitigating biases and ensuring responsible AI-generated content. Prompt Engineering offers coders and software developers a competitive edge by empowering them to develop more effective and efficient AI-driven solutions in their projects. By harnessing the capabilities of cutting-edge AI models like GPT-4, coders can automate repetitive tasks, enhance natural language understanding, and even generate code suggestions, boosting productivity and creativity. In addition, mastering prompt engineering can contribute to improved job security, as professionals with these in-demand skills are highly sought after in the rapidly evolving tech landscape. Quick Start to Prompt Engineering for Coders and Software Developers is a one day course designed to get you quickly up and running with the prompting skills required to out AI to work for you in your development efforts. Guided by our AI expert, you?ll explore key topics such as text preprocessing, data cleansing, GPT-4 tokenization, input formatting, prompt design, and optimization, as well as ethical considerations in prompt engineering. In the hands-on labs you?ll explore tasks such as formatting inputs for GPT-4, designing and optimizing prompts for business applications, and implementing multi-turn conversations with AI. You?ll work with innovative tools like the OpenAI API, OpenAI Codex, and OpenAI Playground, enhancing your learning experience while preparing you for integrating prompt engineering into your professional toolkit. By the end of this immersive course, you?ll have the skills necessary to effectively use prompt engineering in your software development projects. You'll be able to design, optimize, and test prompts for various business tasks, integrate GPT-4 with other software platforms, and address ethical concerns in AI deployment. Generative AI represents an exhilarating frontier in artificial intelligence, specializing in the creation of new data instances, imitation of real data, and content generation. Its remarkable capabilities facilitate automated content creation, enriched user experiences, and groundbreaking solutions across diverse industries, ultimately fueling efficiency and transcending technological limits. By harnessing the power of generative AI, developers can craft dynamic content, produce code and documentation, refine user interfaces, and devise customized recommendations, empowering them to construct highly efficient and custom solutions for a wide range of applications. Designed for experienced programmers, Turbocharge Your Code! Generative AI Boot Camp for Developers is a three-day workshop-style course that teaches you the latest skills and tools required to master generative AI models, transforming the way you approach software development. In today's fast-paced technological landscape, generative AI has emerged as a game-changer, with leading companies like NVIDIA, OpenAI, and Google leveraging its capabilities to push the boundaries of innovation. By learning how to harness the power of generative models such as GANs, VAEs, and Transformer models, you will be able to generate code, documentation, and tests, enhance user interfaces, and create dynamic content that adapts to user needs. Our comprehensive curriculum covers everything from the fundamentals of generative AI to advanced techniques and ethical considerations, including hands-on labs where you will develop and deploy custom models using state-of-the-art AI tools and libraries like TensorFlow and Hugging Face Transformers. Throughout the course you'll focus on practical application and collaboration, building confidence with personalized guidance and real-time feedback from our expert live instructor. Upon completion, you will be equipped with the knowledge and experience necessary to develop and implement innovative generative AI models across various industries, improving existing products, creating new applications, and gaining highly-valuable skills in the rapidly advancing field of AI. ADDITIONAL COURSE DETAILS: Nexus Humans Turbocharge Your Code! Generative AI Boot Camp for Developers (TTAI2305) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Turbocharge Your Code! Generative AI Boot Camp for Developers (TTAI2305) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is appropriate for advanced users, system administrators and web site administrators who want to use Python to support their server installations, as well as anyone else who wants to automate or simplify common tasks with the use of Python scripts. Students can apply the course skills to use Python in basic web development projects or automate or simplify common tasks with the use of Python scripts. Overview This skills-focused course is about 50% hands-on lab to lecture ratio, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert instructor, you'll learn how to: Create working Python scripts following best practices Use python data types appropriately Read and write files with both text and binary data Search and replace text with regular expressions Work with with the standard library and its work-saving modules Create 'real-world', professional Python applications Know when to use collections such as lists, dictionaries, and sets Work with Pythonic features such as comprehensions and iterators Write robust code using exception handling Introduction to Python Programming Basics is a hands-on Python programming course that teaches you the key skills you?ll need to get started with programming in Python to a solid foundational level. The start of the course will lead you through writing and running basic Python scripts, and then guide you through how to use more advanced features such as file operations, regular expressions, working with binary data, and using the extensive functionality of Python modules. Extra emphasis is placed on features unique to Python, such as tuples, array slices, and output formatting. This course provides you with an excellent kick start for users new to Python and scripting, enabling you to quickly use basic Python skills on the job in a variety of ways. You?ll be able use Python in basic web development projects, or use it to automate or simplify common tasks with the use of Python scripts. The course also serves as a solid primer course / foundation for continued Python study in support for next level web development with Python, using Python in DevOps, Python for data science / machine learning or Python for systems admin or networking support. PYTHON QUICK VIEW * What is Python? * Python timeline * Advantages/disadvantages * Installing Python * Getting help THE PYTHON ENVIRONMENT * Starting Python * Using the interpreter * Running a Python script * Editors and IDEs GETTING STARTED WITH PYTHON * Using variables * Builtin functions * String data * Numberic data * Converting types * Console input/output * Command line parameters FLOW CONTROL * About flow control * The if statement * Relational and Boolean operators * while loops * Exiting from loops ARRAY TYPES * About array types * Lists and list methods * Tuples * Indexing and slicing * Iterating through a sequence * Sequence functions, keywords, and operators * List comprehensions and generators WORKING WITH FILES * File overview * Opening a text file * Reading a text file * Writing to a text file DICTIONARIES AND SETS * About dictionaries * Creating dictionaries * Iterating through a dictionary * About sets * Creating sets * Working with sets FUNCTIONS * Defining functions * Returning values * Parameters and arguments * Variable scope SORTING * The sorted() function * Custom sort keys * Lambda functions * Sorting in reverse * Using min() and max() ERRORS AND EXCEPTION HANDLING * Exceptions * Using try/catch/else/finally * Handling multiple exceptions * Ignoring exceptions MODULES AND PACKAGES * Creating Modules * The import statement * Module search path * Using packages * Function and module aliases GETTING STARTED WITH OBJECT ORIENTED PROGRAMMING AND CLASSES * About object-oriented programming * Defining classes * Constructors * Understanding self * Properties * Instance Methods and data * Class methods and data * Inheritance ADDITIONAL COURSE DETAILS: Nexus Humans Introduction to Python Programming Basics (TTPS4800) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Introduction to Python Programming Basics (TTPS4800) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for The ideal audience for the RPA and UiPath Boot Camp is beginners in the field of RPA and individuals in roles such as developers, project managers, operation analysts, and tech enthusiasts looking to familiarize themselves with automation technologies. It's also perfectly suited for business professionals keen on understanding and implementing automated solutions within their organizations to optimize processes. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Automation Learning expert instructor, students will explore: Gain a thorough understanding of Robotic Process Automation (RPA) and its applications using UiPath, setting a solid foundation for future learning and application. Learn to record and play in UiPath Studio, a key skill that enables automating complex tasks in a user-friendly environment. Master the art of designing and controlling workflows using Sequencing, Flowcharting, and Control Flow, helping to streamline and manage automation processes effectively. Acquire practical skills in data manipulation, from variable management to CSV/Excel and data table conversions, empowering you to handle data-rich tasks with confidence. Develop competence in managing controls and exploring various plugins and extensions, providing a broader toolkit for handling diverse automation projects. Get hands-on experience with exception handling, debugging, logging, code management, and bot deployment, fundamental skills that ensure your automated processes are reliable and efficient. How to deploy and control Bots with UiPath Orchestrator The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. WHAT IS ROBOTIC PROCESS AUTOMATION? * Scope and techniques of automation * Robotic process automation * About UiPath * The future of automation RECORD AND PLAY * UiPath stack * Downloading and installing UiPath Studio * Learning UiPath Studio * Task recorder * Step-by-step examples using the recorder SEQUENCE, FLOWCHART, AND CONTROL FLOW * Sequencing the workflow Activities * Control flow, various types of loops, and decision making * Step-by-step example using Sequence and Flowchart * Step-by-step example using Sequence and Control flow DATA MANIPULATION * Variables and scope * Collections * Arguments ? Purpose and use * Data table usage with examples * Clipboard management * File operation with step-by-step example * CSV/Excel to data table and vice versa (with a step-by-step example) TAKING CONTROL OF THE CONTROLS * Finding and attaching windows * Finding the control * Techniques for waiting for a control Act on controls ? mouse and keyboard activities * Working with UiExplorer * Handling events * Revisit recorder * Screen Scraping * When to use OCR * Types of OCR available * How to use OCR * Avoiding typical failure points TAME THAT APPLICATION WITH PLUGINS AND EXTENSIONS * Terminal plugin * SAP automation * Java plugin * Citrix automation * Mail plugin * PDF plugin * Web integration * Excel and Word plugins * Credential management Extensions ? Java, Chrome, Firefox, and Silverlight HANDLING USER EVENTS AND ASSISTANT BOTS * What are assistant bots? * Monitoring system event triggers * Monitoring image and element triggers * Launching an assistant bot on a keyboard event EXCEPTION HANDLING, DEBUGGING, AND LOGGING * Exception handling * Common exceptions and ways to handle them * Logging and taking screenshots * Debugging techniques * Collecting crash dumps * Error reporting MANAGING AND MAINTAINING THE CODE * Project organization * Nesting workflows * Reusability of workflows * Commenting techniques * State Machine * When to use Flowcharts, State Machines, or Sequences Using config files and examples of a config file * Integrating a TFS server DEPLOYING AND MAINTAINING THE BOT * Publishing using publish utility * Overview of Orchestration Server * Using Orchestration Server to control bots * Using Orchestration Server to deploy bots * License management * Publishing and managing updates

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

Learn the basics of Data Science, combining a supported #CISCO Skills for All online course with practical learning and a project to help consolidate the learning.