Are you ready to take the PCPP1 – Certified Professional in Python Programming 1 exam? This course is in the form of practice tests and consists of 300 questions that may appear during the PCPP1 – Certified Professional in Python Programming 1 exam. Where necessary, explanations are added to the questions. This course allows you to confirm your proficiency and give you the confidence you need to earn the PCPP1 – Certified Professional in Python Programming 1 certification. PCPP1 – Certified Professional in Python Programming 1 certification is a professional credential that measures the candidate's ability to accomplish coding tasks related to advanced programming in the Python language and related technologies, advanced notions and techniques used in object-oriented programming, the use of selected Python Standard Library modules and packages, designing, building and improving programs and applications utilizing the concepts of GUI and network programming, as well as adopting the coding conventions and best practices for code writing.

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This course is Free to Audit and good for understanding more about the ethics behind data science. In this course, you will get to know about the framework to analyze ethical considerations regarding the privacy and control of consumer information and big data. This course will cover the following questions- Who owns data, How do we value privacy, How to receive informed consent, and What it means to be fair.

First, The Data! • Over 1 million unique chat users • Over 150 million conversation data points focused on mental health and emotional wellbeing • Over 1.1 million manually labeled data points by our highly trained moderators • Over 1.2 million data points on moods and emotions • Over 480 thousand resources and services matched in real-time (patented) • Over 10 real-time AI engines Our own corpus and language models (patented) • Double feedback loop from users and moderators for ML and fine tuning • No hate/racism/trolls or other biases in the data, as all user chats supervised by our moderators Supportiv is driven by building a peer-to-peer mental well-being platform that helps users with their emotional needs 24/7/365 affordably. We are seeking a highly-analytical impact-oriented Ph.D. student to join our Data Science team. The role will serve as a core member within the team, focused on applying artificial intelligence (AI) to solve real business problems, along with analytics to drive insights from the user interactions on the platform to guide data-driven product development and business decisions. The Ph.D. student will work cross-functionally between various teams at Supportiv. Please include your resume and transcripts.

You're looking for a complete Artificial Neural Network (ANN) course that teaches you everything you need to create a Neural Network model in Python, right? A Verifiable Certificate of Completion is presented to all students who undertake this Neural networks course. If you are a business Analyst or an executive, or a student who wants to learn and apply Deep learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the most advanced concepts of Neural networks and their implementation in Python without getting too Mathematical. This course covers all the steps that one should take to create a predictive model using Neural Networks. Most courses only focus on teaching how to run the analysis but we believe that having a strong theoretical understanding of the concepts enables us to create a good model .

Many of the online courses teach you to code but not the theory/way of thinking behind it why would we choose a while but not a for loop, why should we pass 2 parameters to a function but not only one? We provide a platform for thousands of people to expand the understanding of programming and computer science. Founded in 2013 our mission is to spread the love for programming. To achieve this, we're working hard on providing content that will help people build a solid foundation in those subjects. This course will help you to master the foundation and know-how to solve problems with Python code.

With the recent global and regional socio-economic disruptions caused by the pandemic, industries such as retail, consumer products, manufacturing, pharmaceutical, and life sciences all struggle to align production and stocking with rapidly shifting purchasing demands. At the same time, some channels have surged ahead: online retailers, delivery services, and pharmacies are thriving. In this latest Data Science Central podcast, we discuss how injecting AI into existing business intelligence solutions can greatly enhance the ability of organizations to predict future demand for goods, even in uncertain and dynamic times.

First, The Data! • Over 1 million unique chat users • Over 150 million conversation data points focused on mental health and emotional wellbeing • Over 1.1 million manually labeled data points by our highly trained moderators • Over 1.2 million data points on moods and emotions • Over 480 thousand resources and services matched in real-time (patented) • Over 10 real-time AI engines Our own corpus and language models (patented) • Double feedback loop from users and moderators for ML and fine tuning • No hate/racism/trolls or other biases in the data, as all user chats supervised by our moderators Supportiv is driven by building a peer-to-peer mental well-being platform that helps users with their emotional needs 24/7/365 affordably. We are seeking a highly-analytical impact-oriented Ph.D. student to join our Data Science team. The role will serve as a core member within the team, focused on applying artificial intelligence (AI) to solve real business problems, along with analytics to drive insights from the user interactions on the platform to guide data-driven product development and business decisions. The Ph.D. student will work cross-functionally between various teams at Supportiv. We are not just a highly ambitious technology company with a soul.

Role requiring'No experience data provided' months of experience in None Combine two of the fastest-growing fields on the planet with a culture of performance, collaboration and opportunity and this is what you get.

In this advanced course on deep reinforcement learning, you will learn how to implement policy gradient, actor critic, deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and soft actor critic (SAC) algorithms in a variety of challenging environments from the Open AI gym. There will be a strong focus on dealing with environments with continuous action spaces, which is of particular interest for those looking to do research into robotic control with deep reinforcement learning. Rather than being a course that spoon feeds the student, here you are going to learn to read deep reinforcement learning research papers on your own, and implement them from scratch. You will learn a repeatable framework for quickly implementing the algorithms in advanced research papers. Mastering the content in this course will be a quantum leap in your capabilities as an artificial intelligence engineer, and will put you in a league of your own among students who are reliant on others to break down complex ideas for them.