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Welcome to the AI and ML Enthusiast Course: Building a Face Recognition Web App with Django, Machine Learning, and Cloud Deployment on AWS! Embark on an exciting journey into Artificial Intelligence as we delve into the realms of Computer Vision and Face Recognition within the expansive field of AI and ML. This course is designed to guide you through the entire development process of an end-to-end project, catering to both machine learning and web development enthusiasts. Course Phases: Phase 1: Machine Learning - Face Identity Recognition - Image processing techniques with OpenCV - Prerequisites of the course: Python installation and library setup - Face Detection using OpenCV and Deep Neural Networks - Feature extraction using deep neural networks - Training machine learning models: logistic regression, support vector machines, random forest - Combining models with a Voting Classifier (stacking method) - Model selection and hyperparameter tuning for face recognition Phase 2: Machine Learning - Facial Emotion Recognition - Application of machine learning techniques from face identity recognition - Integration of detection and recognition models into a pipeline Phase 3: Django Web App Development - Web application development in Django - Rendering HTML, CSS, and Bootstrap for the frontend - Backend development in Python using the MVT (Models, Views, and Templates) framework - Designing a SQLite database for the Django app - Interfacing machine learning pipeline models with the MVT framework - Styling the app using Bootstrap Phase 4: Deployment / Production on AWS Cloud - Deployment of the Django Web App on AWS Elastic Beanstalk - Utilizing the AWS Free Tier for 12 months - Accessing the app globally through a provided URL/domain - Troubleshooting and error resolution during deployment Course Highlights: - In-depth learning of OpenCV for image processing - Training models for Face Recognition and Facial Emotion Recognition - Django web app development with MVT framework - Integration of machine learning models into the web app - Deployment on AWS Elastic Beanstalk with a focus on the AWS Free Tier If you aspire to be an AI developer, this course is your gateway to mastering AI and ML concepts while gaining hands-on experience. Don't miss out – start your journey now! See you inside the course!

Step into the cutting-edge intersection of law and technology with the "Prompt Engineering for Law" specialization, designed for legal professionals seeking to harness the power of Generative AI. This course introduces the foundations of Generative AI, exploring its burgeoning role in legal applications from contract analysis to litigation support. Dive into the ethical considerations and privacy concerns intrinsic to the legal profession, and gain proficiency in crafting targeted prompts to leverage AI in augmenting your legal practice efficiently. Prepare not just for the changes at hand, but for a future of perpetual advancement, cultivating a mindset of ceaseless curiosity that empowers you to adapt and thrive alongside rapid technological evolution. Whether enhancing due diligence processes or synthesizing complex legal research, you will emerge from this specialization as an innovator, ready to carve a niche in the technologically driven landscape of law. Applied learning project Throughout the specialization, students will participate in hands-on exercises that involve developing, testing, and refining prompts to effectively utilize Generative AI in ways that can be leveraged for streamlining legal research, drafting documents, and enhancing due diligence efforts.

In this specialization, students will be introduced to the fundamentals and history of ESG investing and will take a close look at a range of investment approaches based on environmental, social, and governance factors. You will learn about the five materiality pathways and how they interact with ESG metrics. You will explore the concepts of positive and negative screening and identify ESG factors that cause investors to reject or negatively screen certain assets. Next, you will look at private environmental governance, the active role that private companies play in combating climate change, and the parallels between the public and private sectors. Finally, you will assess the effectiveness of corporate authenticity and the influence of politics in shaping corporate ESG policy, as well as the importance of establishing independent directors to maintain neutrality and protect stakeholder interests. By the end of this specialization, you will understand best practices for creating a robust risk management plan, understand sophisticated indexing and measurement methods used in the ESG space, explore climate disclosure and climate action, and how social activism is impacting the corporate world in the 21st century. Applied learning project Each course module in this specialization concludes with an assessment. These assessments are designed to test learners' knowledge and provide them with the opportunity to apply course concepts such as investment analytics, indexing tools, and critical analysis of ESG policies, activism, and greenwashing. The assessments will be cumulative and cover ESG investing fundamentals, public and private governance, and sustainability factors, allowing you to build a diverse and risk-resilient ESG portfolio.

The job market for business intelligence (BI) analysts is expected to grow 23 percent from 2021 to 2031 (U.S. Bureau of Labor Statistics). This IBM specialization gives you the in-demand skills employers are looking for when hiring a BI analyst. BI analysts collect, clean, and analyze key business data to find patterns and insights that help make business decisions. In this specialization, you'll learn the fundamentals of SQL, focusing on querying relational databases with this popular and powerful language. You'll use core Linux commands to create basic shell scripts . You'll also learn how to create and automate ETL, ELT, and data pipelines using Bash scripts, Apache Airflow, and Apache Kafka . You'll learn why companies use data lakes and data maps, and how to work with a data warehouse . You'll also dive into the useful side of BI by creating interactive reports and dashboards so you can extract value from the data stored in your warehouse. Plus, you'll gain valuable hands-on practice using real tools used by data professionals. Each course is packed with hands-on assignments and includes a project that will give you something to talk about in an interview. Once you complete the full course, you will have a portfolio of projects and a certificate of specialization for your resume and LinkedIn profile . Get started in the in-demand field of business analytics. Enroll today. Applied learning project Using the course's hands-on labs and projects, hosted in cloud environments, you'll gain work-ready experience with the following real-world tools and tasks: - Writing SQL queries and creating joins using PostgreSQL, MySQL and DB2 databases - Executing Commands and Pipes in Linux, Creating Shell Scripts - Scheduling jobs with cron, building ETL and data pipelines, creating and monitoring Airflow DAGs, working with streaming data using Kafka - Designing Data Warehouses Using Star and Snowflake Schemas - Data quality check, loading of staging and production storages - Developing cubes, rollups and materialized views/tables - Create interactive reports and dashboards - Analyze warehouse data using BI tools such as Cognos Analytics

In today’s interconnected world, basic knowledge of IT hardware, software, networking, cybersecurity, and cloud computing is vital for nearly every function or role in an organization. Adding memory, updating an operating system, connecting to a network, recognizing phishing, and configuring cloud technologies are just a few of the skills employees need or need help with. This five-course specialization provides essential skills for nearly every IT job, including technical support specialist, data analyst, data scientist, artificial intelligence specialist, web developer, software engineer, systems administrator, DevOps and site reliability engineer, data center technician, network specialist, IT manager, and cybersecurity analyst. You will gain knowledge and skills in hardware, operating systems, programming, databases, networking, storage, cybersecurity and cloud computing that will prepare you for entry-level IT work or help you better understand and manage IT responsibilities within your organization. In addition to earning an IBM certification upon successful completion of this specialization, it provides the dual benefit of preparing you for the CompTIA IT Fundamentals (IFT+) certification exam, which can validate your skills, helping you gain a competitive advantage. This program is designed for beginners. No prior IT background, programming experience, or cloud skills are required to begin this program. All that is needed is basic computer literacy. Applied learning project These assignments are designed for beginners and allow you to gain the basic skills from each course. You'll use interactive activities and reference materials to identify computer hardware, ports, and peripherals, and review the steps involved in setting up a workstation, installing an operating system, and configuring frequently changed operating system settings. In hands-on labs, you'll use Python to build fundamental programming skills that are relevant in the real world, and learn how to perform basic database operations using MySQL. In additional interactive labs, you'll use the IBM Cloud platform and other interactive techniques to work with custom software, back-end applications, introductory networking concepts, security techniques, and cloud computing types and services.

This is the second course in the Google Data Analytics Certificate. You’ll build on your understanding of the topics that were introduced in the first course of this certificate program. The material will help you learn how to ask effective questions, make data-driven decisions, and meet stakeholders’ needs. Current Google data analysts will instruct and provide you with hands-on ways to accomplish common data analytics tasks. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course, you will: - Learn about effective questioning techniques that can help guide analysis. - Gain an understanding of data-driven decision-making and how data analysts present findings. - Explore a variety of real-world business scenarios as an example of questioning and decision-making. - Discover how and why spreadsheets are an important tool for data analysts. - Examine the key ideas associated with structured thinking and how they can help analysts better understand problems and develop solutions. - Learn strategies for managing the expectations of stakeholders while establishing clear communication with a data analytics team to achieve business objectives.

This course is the first of a series that aims to prepare you for a role as an entry-level IT Support Specialist. In this course, you'll be introduced to the world of Information Technology, or IT. You'll learn about the different faces of Information Technology, like computer hardware, the Internet, computer software, troubleshooting, and customer service. This course covers a wide variety of topics in IT that are designed to give you an overview of what's to come in this certificate program. By the end of this course, you'll be able to: ● understand how the binary system works ● assemble a computer from scratch ● choose and install an operating system on a computer ● understand what the Internet is, how it works, and the impact it has in the modern world ● learn how applications are created and how they work under the hood of a computer ● utilize common problem-solving methodologies and soft skills in an Information Technology setting

In the first year of the Machine Learning Specialization, you will: - Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn - Build and train supervised machine learning models for prediction and binary classification problems, including linear regression and logistic regression The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This specialization is taught by Andrew Ng, an AI visionary who has led landmark research at Stanford University and pioneering work at Google Brain, Baidu, and Landing.AI to advance the field of AI. This three-course specialization is an updated and expanded version of Andrew’s groundbreaking machine learning course, which has received a 4.9 out of 5 stars and has been taken by more than 4.8 million students since its introduction in 2012. The course provides a broad overview of modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for AI and machine learning innovation (model evaluation and tuning, a data-driven approach to improving performance, and more.) By the end of this specialization, you’ll master key concepts and gain the practical know-how to quickly and effectively apply machine learning to solve complex, real-world problems. If you’re looking to enter the AI ​​field or build a career in machine learning, the new Machine Learning specialization is the best place to start.

This specialisation has been designed to combine the latest business research in digital transformation and strategy with the latest technical knowledge of the technologies that are changing the way we work and do business, giving you the opportunity to advance your career. By the end of this specialisation, you will have an understanding of three technologies that are impacting all businesses: artificial intelligence, cloud computing and data science. You will also be able to develop or drive a digital transformation strategy for your business using these technologies. This specialisation will help managers understand technology and technical workers understand strategy, and is ideal for anyone who wants the opportunity to help lead digital transformation and technical and business strategy projects. Applied learning project This specialisation has been designed to combine the latest business research in digital transformation and strategy with the latest technical knowledge of the technologies that are changing the way we work and do business, giving you the opportunity to advance your career. By the end of this specialisation, you will have an understanding of three technologies that are impacting all businesses: artificial intelligence, cloud computing and data science. You will also be able to develop or drive a digital transformation strategy for your business using these technologies. This specialisation will help managers understand technology and technical workers understand strategy, and is ideal for anyone who wants the opportunity to help lead digital transformation and technical and business strategy projects.

Data engineering is one of the fastest growing tech jobs, with demand for skilled data engineers far outstripping supply. The goal of data engineering is to make quality data accessible for fact-finding and data-driven decision making. This specialization from IBM will help anyone interested in a career in data engineering by teaching the fundamental skills needed to get started in the field. No prior data science experience is required to successfully complete this specialization. The specialization consists of 5 self-paced online courses covering the skills needed to work with data, including the data engineering ecosystem and lifecycle, Python, SQL, and relational databases. You’ll learn these essential data engineering skills through engaging videos and hands-on labs using real tools and real databases. You’ll develop your understanding of data engineering, gain skills that are directly applicable to a data engineering career, and build the foundation for your data engineering career. Upon successful completion of these courses, you will gain the practical knowledge and experience needed to delve deeper into data engineering and work on more complex data engineering projects. Applied learning project All specialization courses contain a variety of practical laboratory work and assignments that will help you gain practical experience and skills. Projects range from working with data in different formats, transforming and loading this data into a single source, to analyzing socio-economic data using SQL and working with advanced SQL techniques. You will work with various real databases and tools, including MySQL, PostgresSQL, IBM Db2, PhpMyAdmin, pgAdmin, IBM Cloud, Python, Jupyter notebooks, Watson Studio, etc.

If you want to enter the exciting world of software development, then this Software Engineering Fundamentals specialization is for you. No prior degrees or knowledge of programming or application development are required . According to the U.S. Bureau of Labor and Statistics, software developers are in high demand, earning an average salary of $110,140 per year . With a growth rate of 22% in this field, there’s never been a better time to start a career in software development. This program’s self-paced courses provide the foundation for a wide range of IT and software engineering careers , including web development, mobile app development, front-end, back-end, and full stack application development, software testing and quality assurance (QA), and DevOps engineering. This specialization is packed with engaging videos, hands-on labs, and real-world projects that teach fundamental programming principles and the fundamentals of design, architecture, and deployment; the software development life cycle; Git and GitHub repositories; using the Linux terminal and creating Bash shell scripts to automate various tasks; and coding using the Python programming language . The program is suitable for those who are just starting to study software engineering , or for those who would like to get acquainted with the basics of software engineering. It will prepare you to get acquainted with the culture, technologies, and skills necessary to successfully work in the field of software engineering. Applied learning project - Each course is packed with hands-on labs, interactive activities, and projects so you can build your portfolio while gaining practical knowledge of software engineering concepts. Throughout the program, you will develop software engineering skills. Projects include:. - Review job postings to learn about software engineering skills and requirements. - Use Git and GitHub commands to create an open source project, work with branches, merge code, and make pull requests (PRs). - Write a Bash shell script in Linux that creates backups of modified files and schedules it to run every 24 hours using Crontab. - Coding in Python using lists, tuples, dictionaries, sets, conditions, branching, loops, functions, exception handling, objects and classes, web services and APIs, and the NumPy and Pandas libraries. - Develop a Python web application that uses IBM Watson for language translation, including writing unit tests and packaging the application for distribution.

Artificial intelligence is the future of programming. Learn how to use AI tools in practice today. In this course I will show you: - how you develop software with ChatGPT or how AI programs for you . - how to integrate AI into your development environment and develop faster with GitHub Copilot. - how you can use AI to easily translate existing code into other programming languages . - How ChatGPT analyzes technical errors and suggests solutions - the days of Stackoverflow are over! - how AI simplifies your code and rewrites it according to clean code principles . It is a practical course for the daily work as a software developer . We focus on the practical use of AI tools instead of talking about general or theoretical topics from the field of artificial intelligence. AI helps us programmers best when it is integrated directly into the development environment. GitHub Copilot is currently one of the best and most popular AI tools as a plugin for IntelliJ, Visual Studio Code or other development environments. Copilot suggests code, explains existing code, fixes bugs or helps with automated tests. I'll show you the first steps with GitHub Copilot in the course, and more videos are still in the works and will be added later. The examples and exercises in the course are written in the Java programming language and with the Spring Framework. However, the principles and use cases shown apply to all languages. As a software developer and architect, I have been programming for over 15 years. At Deutsche Telekom, I am one of the pioneers in the AI4Coding community. We have developed internal training courses on the topic of AI for developers. In this course, I will let you take part in it in a detailed and optimized form.