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Embark on a comprehensive journey into data analysis with Python and Pandas. Learn to set up Anaconda and Jupyter Lab on macOS and Windows, navigate Jupyter Lab's interface, and execute code cells. - You'll start by mastering essential Python programming concepts, including data types, operators, variables, functions, and classes. - Then, dive into Pandas to create and manipulate Series and DataFrames. The course covers data importing from sources like CSV, Excel, and SQL databases, along with techniques for sorting, filtering, and data extraction. - Advanced analysis methods, including group-by operations, merging, joining datasets, and pivot tables, are also explored to equip you with the skills for efficient and sophisticated data analysis. Ideal for aspiring data analysts and scientists, no prior programming knowledge is necessary with the included Python crash course.

This course advances from fundamental machine learning concepts to more complex models and techniques in deep learning using PyTorch. This comprehensive course covers techniques such as Softmax regression, shallow and deep neural networks, and specialized architectures, such as convolutional neural networks. In this course, you will explore Softmax regression and understand its application in multi-class classification problems. You will learn to train a neural network model and explore Overfitting and Underfitting, multi-class neural networks, backpropagation, and vanishing gradient. You will implement Sigmoid, Tanh, and Relu activation functions in Pytorch. In addition, you will explore deep neural networks in Pytorch using nn Module list and convolution neural networks with multiple input and output channels. You will engage in hands-on exercises to understand and implement these advanced techniques effectively. In addition, at the end of the course, you will gain valuable experience in a final project on a convolutional neural network (CNN) using PyTorch. This course is suitable for all aspiring AI engineers who want to gain advanced knowledge on deep learning using PyTorch. It requires some basic knowledge of Python programming and basic mathematical concepts such as gradients and matrices.

Data visualization is a powerful tool for exploring and communicating insights from data effectively. Seaborn, a Python visualization library built on top of Matplotlib, offers a wide range of features for creating attractive and informative statistical plots. This course provides a comprehensive overview of Seaborn, covering basic plotting techniques as well as advanced statistical visualizations. Participants will learn how to leverage Seaborn to visualize data distributions, relationships, and patterns, enabling them to convey complex information visually with confidence. Data visualization is a powerful tool for exploring and communicating insights from data effectively. Seaborn, a Python visualization library built on top of Matplotlib, offers a wide range of features for creating attractive and informative statistical plots. This course provides a comprehensive overview of Seaborn, covering basic plotting techniques as well as advanced statistical visualizations. Participants will learn how to leverage Seaborn to visualize data distributions, relationships, and patterns, enabling them to convey complex information visually with confidence. Participants should have a basic understanding of Python programming and fundamental data visualization concepts before enrolling in this course. Familiarity with Python's data manipulation libraries such as Pandas, and an introductory knowledge of Matplotlib, will be beneficial. This fundamental knowledge will enable learners to quickly grasp Seaborn's functionalities and apply them effectively in their data visualization tasks. By the end of this course, learners will be equipped to explain the critical role of data visualization in data analysis and interpretation. They will gain practical skills in creating basic plots using Seaborn to visualize data distributions and relationships. Additionally, learners will explore advanced statistical plots for deeper data analysis and develop the ability to customize and enhance Seaborn visualizations, ensuring their data stories are communicated clearly and impactfully.

This course has been designed for individuals seeking entry-level positions in IT support. Whether you're a recent graduate, a career changer, or someone looking to kickstart your career in the tech industry, it will provide you with the fundamental knowledge and practical skills needed to excel in this field. In this course, you'll consolidate your learning into action using a number of troubleshooting approaches. You'll learn about troubleshooting issues relating to both hardware and software, as well as system-related issues across multiple operating systems. You'll examine diagnostic tools to combat networking issues as well as system performance. Your skills are then showcased in the capstone project, where you will engage with a real-world scenario. You'll be provided with multiple diagnostic outputs and will be tasked with identifying the issue and recommending a solution. You'll also be required to document and communicate the troubleshooting process and outcome. After completing this course, you'll be able to: • Apply a systematic approach to diagnose technical issues across different hardware and software environments • Implement troubleshooting skills to resolve problems effectively • Utilize diagnostic tools and techniques for problem resolution This is also a great way to prepare for the Microsoft MS-900 exam. By passing the MS-900 exam, you'll earn the Microsoft 365 Fundamentals certification.

This course will help you perform data cleansing and analysis efficiently using Alteryx. Starting with an introduction to Alteryx, it covers installation, user interface, and data import/export from Excel and CSV files. You'll explore data cleansing and filtering using the Preparation tab, and understand the role of the Join tab. The course also covers working with the Parse and Transform tabs and utilizing the Reporting tab. Additionally, you'll learn about the Documentation tab's tools and review case studies to solidify your learning. By the end, you'll be proficient in using Alteryx for real-world data tasks. Key skills include data retrieval, appending, merging with joins, data cleaning for BI tools, data visualization, and using the RegEx tool. The course is ideal for data professionals seeking a powerful tool for quick and easy data cleaning and analysis. Basic knowledge of Excel VLOOKUP, functions, formulas, and joins is recommended.

This course uses the latest mobile technology and job tools like React Native, JavaScript, Expo-GO, and 2023 conventions, teaching advanced mobile development with React hooks. In this course, you will: - Leverage ChatGPT, Stack Overflow, and documentation, it simplifies coding tasks and enhances skills. - Develop a project from scratch, learning web application development with ChatGPT, React Native, and JavaScript, focusing on OOP, functional components, and React Hooks. - Cover building sleek, functional UIs, writing templated code, and documenting processes. - Create a complete mobile app with a client-side simulated database using ChatGPT, ultimately deploying a functional app to their phones. This course is perfect for mobile developers with basic knowledge of JavaScript and React Native. Familiarity with mobile app development and an interest in AI are recommended but not required.

ChatGPT enhances programming and code analysis, offering significant early advantages. This course teaches you to create an AI-powered pet name generator. Starting with ChatGPT and the latest web development tools, you'll install the necessary tools and gain hands-on experience with web technologies. You will: - Learn to implement machine learning in a real-world project - Use React Hooks for interactive interfaces, and make API calls to OpenAI using Fetch and NPX. - Build an AI application, understand machine learning, - Create React Hook-based interfaces, adding a pet name generator to your portfolio. - Learn to build an AI app with OpenAI API, - Install tools and dependencies, and get hands-on with React, Next.js, JavaScript, Node, and CSS. Ideal for those interested in web development and ChatGPT jobs, this course suits beginners and those with basic JavaScript knowledge. No programming experience is needed, but basic JavaScript and web development knowledge is a plus.

In this course, you'll learn to install VMware and create a virtual environment with both hacker and target labs. You'll master advanced information gathering and reconnaissance in both active and passive modes, and receive templates and guides for professionally storing data. Using this data: - You'll conduct vulnerability assessments and leverage the Metasploit framework for easier exploitation, while also learning manual techniques. - You'll tackle security on custom websites with vulnerabilities like SQL injection, XSS, unrestricted file uploads, command injection, and brute forcing. - Post-exploitation methods with and without Metasploit, as well as manual privilege escalation techniques, will help you gain full root/admin access. The final section focuses on writing professional penetration testing reports. By the end, you'll be ready for professional penetration testing. This course is ideal for those curious about hacking, aspiring pentesters, and students exploring security testing. Basic Linux, networking, and hacking knowledge are advantageous.

This course provides a beginner's guide to using Maven and SonarQube in a DevOps environment. You'll start with an introduction to Maven, learning to set up environments on Windows and Linux and build Java projects. In this, you will: - Cover Maven coordinates, default directory structure, goals, and setting up servers. - Integrate Maven into a DevOps workflow with Jenkins, build projects, and WAR files. - Explore SonarQube, including installation on EC2, and integration with PostgreSQL, and Jenkins. - Create AWS accounts, Installing Git Bash, MobaXterm, and Tomcat. Designed for aspiring DevOps engineers, software developers, and IT professionals, this course ensures hands-on experience with video tutorials and practical demonstrations. Basic Linux, Git, and AWS EC2 knowledge is recommended for best results. By the end, you'll have a solid understanding of Maven and SonarQube, and how to integrate these tools into DevOps pipelines effectively.

This course provides a guide to digital forensics for penetration testers, featuring hands-on labs and video tutorials. Starting with setting up a forensic lab using VirtualBox, you'll learn to create virtual installations of CSI Linux, Kali Linux, and Windows 10. - You'll master forensic tools like Kali Forensic Mode, Autopsy, and Shodan, gaining hands-on experience in acquiring and analyzing forensic disk images, managing digital forensics cases, and conducting OSINT investigations. - You'll also delve into reverse engineering malware using Ghidra and performing network forensics with Wireshark. - The course culminates in Capture the Flag exercises to apply your skills in real-world scenarios. By the end, you'll have a robust understanding of digital forensics processes, making you a proficient penetration tester. Designed for aspiring and professional penetration testers, cybersecurity analysts, and IT professionals with basic networking and cybersecurity knowledge, this ensures practical, real-world experience through interactive learning. This course is tailored for technical professionals, cybersecurity enthusiasts, and pentesters seeking to deepen their expertise in digital forensics. Participants should have a fundamental understanding of networking and basic Linux operations. Familiarity with virtual environments and command-line interfaces will be beneficial but not mandatory.

Are you ready to become a deep learning expert? This step-by-step course guides you from basic to advanced levels in deep learning using Python, the hottest language for machine learning. Each tutorial builds on previous knowledge and assigns tasks solved in the next video. You will: - Learn to train machines to predict like humans by mastering data preprocessing, general machine learning concepts, and deep neural networks (DNNs). - Cover the architecture of neural networks, the Gradient Descent algorithm, and implementing DNNs using NumPy and Python. - Understand DNN methodologies with real-world datasets, such as the IRIS dataset. Designed for those interested in data science or advancing their skills in DNNs, this course requires a background in deep learning and a basic understanding of Python and mathematics will be helpful. It's clear and beginner-friendly, teaching theoretical concepts followed by practical implementation.

In this course, you'll learn to set up your Kali Linux 2.0 lab, understand device communication, and master Man in the Middle (MITM) attacks. The course has four sections: - Preparation, where you download and set up Kali Linux as a virtual machine or main OS; - Network Basics, covering essential network knowledge for security testing; - MITM Attack, teaching you to perform MITM attacks and execute post-modules like playing music on the target OS, stealing credentials, and gaining full access to connected devices; - Protecting Yourself, learning to safeguard your OS against these attacks. By the end, you'll perform MITM attacks on target networks, control connected computers, and protect yourself. You'll learn to navigate the Linux environment, explore Kali tools, learn ARP poisoning, access client accounts in Wi-Fi networks, and launch MITM attacks. This course is designed for cybersecurity enthusiasts, ethical hackers, and IT professionals looking to deepen their knowledge of network security. A basic understanding of Linux and networking concepts is recommended but not required.