In this lecture, I'll share with you the specific advice I got that completely changed how I read overnight. It's another huge mindset shift you need to apply that I learned from a multi-millionaire guest speaker in one of my classes in college. I'm so lucky I went to class that night.

The best job to have in 2017 according to Glassdoor? The #1 skill you need to start a career in Data Science? So, if you are interested in a career in data science, algorithmic trading, robotics, or any industry where human labor is getting replaced by machines, you have come to the right place! We have prepared an amazing course not only to get you acquainted with, but help you understand how deep machine learning works! Worried you have no experience?

Artificial Intelligence (AI) technology is increasingly prevalent in our everyday lives. It has uses in a variety of industries from gaming, journalism/media, to finance, as well as in the state-of-the-art research fields from robotics, medical diagnosis, and quantum science. In this course you'll learn the basics and applications of AI, including: machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.

Recently I completed the Data Engineering on Google Cloud Platform Specialization (link here) through Coursera, here is my review. Only problem was a couple of issues in the final labs of the course. You can take each module out of order or complete sequentially. Its up to you, I'd recommend to keep it sequential at least roughly. I went from 1 to 3 then went back to 2, 4 and then 5. The courses are hosted by Valliappa Lakshmanan from Google.

Artificial Intelligence (AI) is one of the most booming topics in every industry. Based on the demand, Artificial Intelligence Courses are offered by a number of massive open online courses (MOOCs) providers like Udemy, Coursera, and edX. Some of this popular MOOC providers offer some in-depth artificial intelligence programs. Majority of these artificial intelligence tutorials are often taught by industry top AI researchers or experts. However, these courses are cheaper compared to the university courses.

Thank you all for the huge response to this emerging course! We are delighted to have over 300 students in over 145 different countries. I'm genuinely touched by the overwhelmingly positive and thoughtful reviews. It's such a privilege to share and introduce this important topic with everyday people in a clear and understandable way. I'm also excited to announce that I have created real closed captions for all course material, so weather you need them due to a hearing impairment, or find it easier to follow long (great for ESL students!)... I've got you covered.

Our world is advancing at an extremely rapid rate. Technologies such as artificial intelligence, machine learning, drones, internet of things, augmented reality, and blockchain are growing in popularity every single day. Personally, I feel another industrial revolution is approaching quickly and the world we will in is going to drastically change. Blockchain is a difficult technology to understand but it has the potential to impact many organizations across the globe. If you're looking to get a head start on an innovative idea that will change our world then you're in the right place!

Then this course is for you! This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way. We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. This course is fun and exciting, but at the same time we dive deep into Machine Learning.

Although compelling assessments have been examined in recent years, more studies are required to yield a better understanding of the several methods where assessment techniques significantly affect student learning process. Most of the educational research in this area does not consider demographics data, differing methodologies, and notable sample size. To address these drawbacks, the objective of our study is to analyse student learning outcomes of multiple assessment formats for a web-facilitated in-class section with an asynchronous online class of a core data communications course in the Undergraduate IT program of the Information Sciences and Technology (IST) Department at George Mason University (GMU). In this study, students were evaluated based on course assessments such as home and lab assignments, skill-based assessments, and traditional midterm and final exams across all four sections of the course. All sections have equivalent content, assessments, and teaching methodologies. Student demographics such as exam type and location preferences are considered in our study to determine whether they have any impact on their learning approach. Large amount of data from the learning management system (LMS), Blackboard (BB) Learn, had to be examined to compare the results of several assessment outcomes for all students within their respective section and amongst students of other sections. To investigate the effect of dissimilar assessment formats on student performance, we had to correlate individual question formats with the overall course grade. The results show that collective assessment formats allow students to be effective in demonstrating their knowledge.