This course is designed to get you ready to take and pass PCEP Certified Entry-Level Python Programmer Certification Exam in the next 7 days! It includes and covers an overview of the PCEP methodology used in a project environment. The majority of people that consider Python as a qualification do so for career and personal development reasons. Master Python and pass PCEP on your first try.
- Access 22 lectures & 4 hours of content 24/7
- Develop impressing Python applications in a few minutes/hours
- Add Python 3 to your resume by understanding advanced object-oriented programming (OOP)
- Create programs using your logic & data structures
- Learn how to program the right way
- Automate coding tasks by building custom Python functions
- Use Loops to improve efficiency, save time, & maximize productivity
Hypotheses (explanations for things that are yet to be proved) are an important facet of data science, as they help to drive innovation and progress. This course will show you how to strengthen your hypotheses by supporting your claims with statistical evidence. From a foundational understanding of the concepts underlying hypothesis testing to working through lots of different, practical examples, and even coding your own testing framework from the ground up, you will have everything that you need to create bullet-proof hypotheses.
- Access 22 lectures & 2 hours of content 24/7
- Learn what random variables are
- Learn what probability distributions (including Gaussian/Normal)
- Familiarize yourself with z-tests
- Familiarize yourself with t-tests
In addition to handling vast amounts of batch data, Spark has extremely powerful support for continuous applications, or those with streaming data that is constantly updated and changes in real-time. Using the new and improved Spark 2.x, this course offers a deep dive into stream architectures and analyzing continuous data. You’ll also follow along a number of real-world examples, like analyzing data from restaurants listed on Zomato and real-time Twitter data.
- Access 36 lectures & 2 hours of content 24/7
- Familiarize yourself w/ Spark 2.x & its support for continuous applications
- Learn how to analyze data from real-world streams
- Analyze data from restaurants listed on Zomato & real-time Twitter data
The Google Cloud Platform is not the most popular cloud offering out there (hello AWS!) but it may be the best cloud offering for high-end machine learning applications. That’s because TensorFlow, the extremely popular deep learning technology is also from Google. This comprehensive guide to TensorFlow and the Google Cloud Platform will help put you on certification track to become a Google Data Engineer or Cloud Architect.
- Access 233 lectures & 28 hours of content 24/7
- Cover the material you need to pass Google Data Engineer & Cloud Architect certification exams
- Explore AppEngine, Kubernetes, & Compute Engine
- Discuss Big Data & Managed Hadoop w/ Dataproc, Dataflow, BigTable, BigQuery, & more
- Learn what neural networks & deep learning are, how neurons work, & how neural networks are trained
- Understand DevOps principles like StackDrive logging, monitoring, & cloud deployment management
- Discover security, networking, & Hadoop foundations
Most businesses use Excel as a basic tool for decision-making and modeling, but what happens when you have too much data to use an Excel spreadsheet? It’s time to move to a database. This course will help you make the move without being intimidated by the new environment. You’ll dive deep into seemingly complex topics like joins, aggregate operators, and interfacing with databases.
- Access 68 lectures & 14 hours of content 24/7
- Learn queries in detail & steer clear of career-limiting mistakes
- Get help from quirky learning tools: repetition, zooming out to remember the big picture, quizzes, a peppy soundtrack & art
- Study database fundamentals & “just enough” theory
- Explore large datasets & uncover insights
- Model & create a database for day-to-day use
- Interface with databases from a programming language such as Python
- Load data & use both GUI and a command-line interface for database operations
This practical, hands-on course was created for newbies – that’s to say, people with no prior training or knowledge with JavaScript or Web Development. Blending practical work with solid theoretical training, this course takes you from the basics of JavaScript through to mastery. This class gives you foundational training on JavaScript so you can increase your coding skills and start pursuing a career in a field that is increasingly in demand as the global reliance on technology grows. Even if you already have some experience, or want to learn about the advanced features of JavaScript, this course is for you!
- Access 59 lectures & 6 hours of content 24/7
- Learn JavaScript coding basics
- Work with variables & operators
- Do string & number manipulation
- Learn with blended practical work & theoretical training
Java is one of the most prominent programming languages today due to its power and versatility. In this course, LearnWhilePracticing guides you to be operational right away. This class will help you uncover new skills through practice, instead of going over a boring class where you would not be grasping the concepts. Practices make perfect! Oracle Certified Java Expert, Mr. Lawrence Decamora guides you throughout the whole course. Learn the basics of Java and start writing your own Java program in no time.
- Access 168 lectures & 20 hours of content 24/7
- Learn the essentials of Java
- Understand the difference between a Class & an Object
- Know the use of an Integrated Development Environment (IDE)
- Explore the fundamental concepts of Java
- Build a GUI-based desktop application
- Start working with Java™ database connectivity (JDBC)
“I started this course with no prior knowledge of Java and even coding. It’s really amazing what 20 hours of immersing yourself in the Java world can get you. The instructor was very engaging and his demonstrations were very detailed. The pacing of the lessons was on point and each video makes sure you understand each concept before moving on to the next one. I totally recommend this course to anyone that’s interested in coding!” – Lian Manongsong
You may be just getting started or have already started to learn how to build projects with your Raspberry Pi. But knowing what to do first and which path to follow can be quite hard, and you may feel stuck. This course will focus on the “why” and make you much more autonomous with your Raspberry Pi, so you will be able to start your own projects without having to desperately search for code to copy/paste on the Internet. This complete hands-on, step-by-step course targets the latest version of Raspberry Pi, the Raspberry Pi 4. Note that everything also works perfectly for Raspberry Pi 2 and 3 versions.
- Access 95 lectures & 9 hours of content 24/7
- Master your Raspberry Pi, starting from scratch
- Build a complete surveillance & alarm project with Raspberry Pi
- Learn Python 3 from zero
- Use the Raspberry Pi’s GPIOs to control hardware components
- Create a web server on your Raspberry Pi
Probability – the ability to predict the likelihood of an event occurring – is crucial knowledge for anyone interested in data science and analysis. Probability has innumerable applications in a wide variety of fields – including comprising of the core of many machine learning and data science algorithms.
From a basic understanding of Probability fundamentals and common terminology to understanding conditional probability and Bayes Theorem, this course will provide you with all you need to begin making accurate predictions. Finally, you will apply your knowledge by building a Naïve Bayes Classifier that predicts whether or not a flight will arrive on time using a set of real-world data.
- Access 13 lectures & 1 hour of content 24/7
- Apply probability ideas on data science &analysis
- Learn the fundamentals of probability
- Learn common terminologies
- Understand conditional probability
- Familiarize with the Bayes Theorem
- Make accurate predictions
- Apply your knowledge by building a Naïve Bayes Classifier
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