The Data Science Course 2020: Complete Data Science Bootcamp
Data science is a multidisciplinary field. It encompasses a wide range of topics. Understanding of the data science field and the type of analysis carried out Mathematics, Statistics, Python, Applying advanced statistical techniques in Python, Data Visualization, Machine Learning, Deep Learning. Each of these topics builds on the previous ones. And you risk getting lost along the way if you don’t acquire these skills in the right order. So, in an effort to create the most effective, time-efficient, and structured data science training available online, we created The Data Science Course 2020.
Statistics is the driving force in any quantitative career. It is the fundamental skill data scientists need to be able to understand and design statistical tests and analyses performed by modern software packages and programming languages. In this course, we start from the very basics of statistics and gradually build up your statistical thinking, enabling you to understand the more complex analyses carried out later in the program.
In Data Science mainly relies on working with two types of data - cross-sectional and time series. This course will help you master the latter by introducing you to ARMA, Seasonal, Integrated, MAX and Volatility models as well as show you how to forecast them into the future.
R Programming for Statistics and Data Science 2020
R is one of the best programming languages specifically designed for statistics and graphics. Programming in R is a fast and effective way to perform advanced data analyses and manipulations. In this course, you will learn how to use R and utilize the many data analysis techniques, methods, and functions it has to offer to the professional data scientist.
Python + SQL + Tableau: Integrating Python, SQL, and Tableau
While Python is the leading programming language for data science, SQL is unmatched when it comes to relational database management. Tableau, on the other hand, is a leading business intelligence software, providing tools for quick computations and rich visualizations. This course will show you how to combine these software products to solve real-life business problems.
This is the Python course that will not only develop your programming skills, but will also give you a problem solving superpower using Python code! In this course you will develop a thorough understanding of Python, how to program in Python, and how to think computationally. You will learn how to implement object-oriented programming (OOP), how to create Python charts in Matplotlib, and how to work with different IDEs like Spyder and Jupyter. While you’re learning, you’ll get to practice your skills with fun and challenging exercises like solving the Sierpinski Triangle and the Towers of Hanoi. Finally, your instructor, Giles McMullen-Klein, is a British programmer who went to Oxford University and used Python for his research there. He’s motivating, enthusiastic, and truly passionate about Python!
Customer Analytics in Python is where marketing and data science meet. Data science and marketing are two of the key driving forces that help companies create value and stay on top in today’s fast-paced economy. This course is packed with knowledge, and includes sections on customer and purchase analytics, as well as a deep-learning model, all implemented in Python.
Credit risk modeling is the place where data science and fintech meet. It is one of the most important activities conducted in a bank and the one with the most attention since the recession. This course is the only comprehensive credit risk modeling course in Python available right now. It shows the complete credit risk modeling picture, from preprocessing, through probability of default (PD), loss given default (LGD) and exposure at default (EAD) modeling, and finally finishing off with calculating expected loss (EL).
Machine and deep learning are some of those quantitative analysis skills that differentiate the data scientist from the other members of the team. The field of machine learning is the driving force of artificial intelligence. This course will teach you how to leverage deep learning and neural networks from this powerful tool for the purposes of data science. The technology we employ is TensorFlow 2.0, which is the state-of-the-art deep learning framework.
Python for Finance: Investment Fundamentals & Data Analytics
We are proud to present Python for Finance: Investment Fundamentals and Data Analytics – one of the most interesting and complete courses we have created so far. It took our team slightly over four months to create this course, but now, it is ready and waiting for you.
Data science is based on statistics and statistics steps on the foundations laid by probability. This course will help you master probability theory necessary to think like a data scientist. You will learn about expected values, combinatorics, Bayesian notation, and probability distributions.
The Power BI Course is designed for students who like to learn by doing. Packed with real-life business scenarios along with quizzes and projects to build, this course will give you the solid understanding required to jump start your career as a Power BI developer, business intelligence analyst, or a multiskilled data scientist. It will not only teach you how to create stunning dashboards but will also introduce you to data modelling and data transformations. You will learn how to write DAX, set up calculated columns and measures, generate roles, and, of course, share your dashboards with your team or clients. Power BI allows you to connect to hundreds of data sources and quickly analyze your data for free.
Machine Learning 101 with Scikit-learn and StatsModels
Advanced proficiency in Microsoft Excel helps you to be faster, more efficient and smarter. It safeguards you from making mistakes when working with numbers. If you want to specialize in Finance, then this is one of the most important skills you need to acquire. In this course, we will teach you how to work with sophisticated formulas, use Pivot tables, and build complex financial models.
SQL - MySQL for Data Analytics and Business Intelligence
SQL is one of the fundamental programming languages you need to learn to work with databases. When you are a data scientist in a company and you need data to perform your analysis, you usually have two options: extract it on your own or contact the IT team. Of course, the ability to extract your own data is an extremely valuable skill to have. In this course, we will teach you everything you need to know in terms of database management and creating SQL queries.
Are you eager to acquire a valuable skill to stay ahead of the competition in this data-driven world?
If the answer is yes, then you have come to the right place at the right time!
Welcome to Web Scraping and API Fundamentals in Python!
The definitive course on data collection!
Web Scraping is a technique for obtaining information from web pages or other sources of data, such as APIs, through the use of intelligent automated programs. Web Scraping allows us to gather data from potentially hundreds or thousands of pages in a really short time.