You can ask around, read Quora answers, or talk to someone in the industry, sure, these methods will supply you with information, but there’s no doubt that this information will be biased towards someone else’s personal experience. How others became data scientists is of little importance to you, I bet. What you’re interested in is whether YOU can become one. Are your skills appropriate for this field? What steps do you need to take to become a successful data scientist? Will your background affect the chances of becoming a data scientist? All valid questions. In this article, we will have a look at the best Data Science course on Udemy in 2020: The Problem Data scientist is one of the best suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace. However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist. And how can you do that? Universities have been slow at creating specialized data science programs. (not to mention that the ones that exist are very expensive and time consuming) Most online courses focus on a specific topic and it is difficult to understand how the skill they teach fit in the complete picture The Solution Data science is a multidisciplinary field. It encompasses a wide range of topics.
“If you’re trying to prepare for an eventual career in finance, but are still looking to round out your knowledge of the subject, The Complete Financial Analyst Course might be a perfect fit for you.”, Business Insider “A Financial Analyst Career is one of the top-paying entry-level jobs on the market.” “Even in the toughest job markets, the best candidates find great positions.”, Forbes You simply have to find a way to acquire practical skills that will give you an edge over the other candidates. But how can you do that? You haven’t had the proper training, and you have never seen how analysts in large firms do their work … Stop worrying, please! We are here to help. The Complete Financial Analyst Course is the most comprehensive, dynamic, and practical course you will find online. It covers several topics, which are fundamental for every aspiring Financial Analyst:
As you can see, this is a complete bundle that ensures you will receive the right training for each critical aspect. Here comes the fun part! We have a challenge for you! After covering each major roadblock, you will be asked to solve a challenge. You will:
Sounds interesting, right? At the end of the challenge, you will send us the work you’ve done, and we will reply with personalized feedback. This makes for an interactive student experience that optimizes what you will learn from the course. What makes this course different from the rest of the Finance courses out there?
Why should you consider a career as a Financial Analyst?
Please don’t forget that the course comes with Udemy’s 30-day unconditional, money-back-in-full guarantee. And why not give such a guarantee, when we are convinced the course will provide a ton of value for you? Welcome to The Business Intelligence Analyst Course, the only course you need to become a BI Analyst. We are proud to present you this one-of-a-kind opportunity. There are several online courses teaching some of the skills related to the BI Analyst profession. The truth of the matter is that none of them completely prepare you. Our program is different than the rest of the materials available online. It is truly comprehensive. The Business Intelligence Analyst Course comprises of several modules:
These are the precise technical skills recruiters are looking for when hiring BI Analysts. And today, you have the chance of acquiring an invaluable advantage to get ahead of other candidates. This course will be the secret to your success. And your success is our success, so let’s make it happen! Here are some more details of what you get with The Business Intelligence Analyst Course:
Sounds amazing, right? Our courses are unique because our team works hard to:
We are proud to present Python for Finance: Investment Fundamentals and Data Analytics – oneof the mostinteresting 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. An exciting journey from Beginner to Pro. If you are a complete beginner and you know nothing about coding, don’t worry! We start from the very basics. The first part of the course is ideal for beginners and people who want to brush up on their Python skills. And then, once we have covered the basics, we will be ready to tackle financial calculations and portfolio optimization tasks. Finance Fundamentals. And it gets even better! The Finance block of this course will teach you in-demand real-world skills employers are looking for. To be a high-paid programmer, you will have to specialize in a particular area of interest. In this course, we will focus on Finance, covering many tools and techniques used by finance professionals daily:
Everything is included! All these topics are first explained in theory and then applied in practice using Python. Is there a better way to reinforce what you have learned in the first part of the course? This course is great, even if you are an experienced programmer, as we will teach you a great deal about the finance theory and mechanics you will need if you start working in a finance context. Teaching is our passion. Everything we teach is explained in the best way possible. Plain and clear English, relevant examples and time-efficient videos. Don’t forget to check some of our sample videos to see how easy they are to understand. If you have questions, contact us! We enjoy communicating with our students and take pride in responding within the 1 business day. Our goal is to create high-end materials that are fun, exciting, career-enhancing, and rewarding. What makes this course different from the rest of the Programming and Finance courses out there?
How important is database management in the age of big data and analytics? It is really important. How many employers would be happy to hire employees who can use data for the purposes of business intelligence? All of them. How many people have these skills? Not enough. This is why now is the time to learn SQL and gain a competitive advantage in the job market. Remember, the average salary of a SQL developer is $92,000! That’s a lucrative career. How come? Well, when you can work with SQL, it means you don’t have to rely on others sending you data and executing queries for you. You can do that on your own. This allows you to be independent and dig deeper into the data to obtain the answers to questions that might improve the way your company does its business. For instance, Database management is the foundation for data analysis and intelligent decision making. Worried that you have no previous experience? Not an issue. We will start from the very basics and gradually teach you everything you need to know. Step by step. With no steps skipped. Why take this course in particular? Isn’t it like the rest of the SQL courses out there? We would like to think it isn’t. Our team worked hard to create a course that is:
Some of these aspects have been covered in other courses. Others haven’t. However, no one provides such a variety of topics in one place. We firmly believe this course is the best training material out there. It is a truly interactive experience preparing you for a real-life working environment. Do you want to learn how to use Excel in a real working environment? Are you about to graduate from university and start looking for your first job? Are you a young professional looking to establish yourself in your new position? Would you like to become your team’s go-to person when it comes to Financial Modeling in Excel? If you answered yes to any of these, then this is the right course for you! Join over 119,002 successful students taking this course! The instructor of this course has extensive experience in Financial Modeling:
Learn the subtleties of Financial Modeling from someone who has walked the same path. Beat the learning curve and stand out from your colleagues. A comprehensive guide to Financial Modeling in Excel:
What we offer:
By completing this course, you will:
Is statistics a driving force in the industry you want to enter? Do you want to work as a Marketing Analyst, a Business Intelligence Analyst, a Data Analyst, or a Data Scientist? Well then, you’ve come to the right place! Statistics for Data Science and Business Analysis is here for you with TEMPLATES in Excel included! This is where you start. And it is the perfect beginning! In no time, you will acquire the fundamental skills that will enable you to understand complicated statistical analysis directly applicable to real-life situations. We have created a course that is:
It is no secret that a lot of these topics have been explained online. Thousands of times. However, it is next to impossible to find a structured program that gives you an understanding of why certain statistical tests are being used so often. Modern software packages and programming languages are automating most of these activities, but this course gives you something more valuable – critical thinking abilities. Computers and programming languages are like ships at sea. They are fine vessels that will carry you to the desired destination, but it is up to you, the aspiring data scientist or BI analyst, to navigate and point them in the right direction. This Python course is different. It will not only teach you Python, it will give you a problem solving super-power using Python code! And that will make all the difference, especially if you are pursuing a career in data science, AI, web development, big data, web testing, or programming for smart devices in Python. The author of this course, Giles McMullen-Klein, is a British programmer who went to Oxford University and used Python for his research there. Giles is one of the best-known Python and data science vloggers on YouTube where more than 133,000 subscribers follow his videos. There are several reasons why this course is different and why Giles could be the perfect Python teacher for you: · Engaging, informative and fun! Giles’ lectures are entertaining and will inspire you to learn Python · Motivating ,enthusiastic and effective – Giles’ passion for coding in Python and teaching the language is infectious · Develop a thorough understanding of Python · Carefully crafted lectures and superb quality of production (Full HD videos) + animations and callouts · Practice, practice, practice – the course contains dozens of exercises to help you master the Python programming concepts covered in the lessons · Giles’ English accent Have you always wanted to learn one of the world’s most popular programming languages? If so, this is the perfect course for you. It will teach you how to program in Python and help to prepare you for coding challenges frequently posed during job interviews. Giles’ teaching style builds a connection with students. And what’s more – he’s there for you if you need any help. Just post any queries or questions in the course Q&A section. In this comprehensive course, we will cover several key topics: ⁃ Why program? Why study Python? ⁃ How to install Python ⁃ Hands-on programming with strings ⁃ Print function ⁃ Variables ⁃ Conditionals ⁃ Loops ⁃ Data structures ⁃ Modules ⁃ Files ⁃ OOP ⁃ Time complexity ⁃ Big O ⁃ Stacks ⁃ Debugging There are many exercises throughout the course, some of our favourites are: ⁃ The Sierpinski Triangle ⁃ The Towers of Hanoi ⁃ And the Computer Vision capstone project Python, SQL, and Tableau are three of the most widely used tools in the world of data science. Python is the leading programming language; SQL is the most widely used means for communication with database systems; Tableau is the preferred solution for data visualization; To put it simply – SQL helps us store and manipulate the data we are working with, Python allows us to write code and perform calculations, and then Tableau enables beautiful data visualization. A well-thought-out integration stepping on these three pillars could save a business millions of dollars annually in terms of reporting personnel. Therefore, it goes without saying that employers are looking for Python, SQL, and Tableau when posting Data Scientist and Business Intelligence Analyst job descriptions. Not only that, but they would want to find a candidate who knows how to use these three tools simultaneously. This is how recurring data analysis tasks can be automated. So, in this course we will to teach you how to integrate Python, SQL, and Tableau. An essential skill that would give you an edge over other candidates. In fact, the best way to differentiate your job resume and get called for interviews is to acquire relevant skills other candidates lack. And because, we have prepared a topic that hasn’t been addressed elsewhere, you will be picking up a skill that truly has the potential to differentiate your profile. Many people know how to write some code in Python. Others use SQL and Tableau to a certain extent. Very few, however, are able to see the full picture and integrate Python, SQL, and Tableau providing a holistic solution. In the near future, most businesses will automate their reporting and business analysis tasks by implementing the techniques you will see in this course. It would be invaluable for your future career at a corporation or as a consultant, if you end up being the person automating such tasks. Our experience in one of the large global companies showed us that a consultant with these skills could charge a four-figure amount per hour. And the company was happy to pay that money because the end-product led to significant efficiencies in the long run. The course starts off by introducing software integration as a concept. We will discuss some important terms such as servers, clients, requests, and responses. Moreover, you will learn about data connectivity, APIs, and endpoints. Then, we will continue by introducing the real-life example exercise the course is centered around – the ‘Absenteeism at Work’ dataset. The preprocessing part that follows will give you a taste of how BI and data science look like in real-life on the job situations. This is extremely important because a significant amount of a data scientist’s work consists in preprocessing, but many learning materials omit that Then we would continue by applying some Machine Learning on our data. You will learn how to explore the problem at hand from a machine learning perspective, how to create targets, what kind of statistical preprocessing is necessary for this part of the exercise, how to train a Machine Learning model, and how to test it. A truly comprehensive ML exercise. Connecting Python and SQL is not immediate. We have shown how that’s done in an entire section of the course. By the end of that section, you will be able to transfer data from Jupyter to Workbench. And finally, as promised, Tableau will allow us to visualize the data we have been working with. We will prepare several insightful charts and will interpret the results together. As you can see, this is a truly comprehensive data science exercise. There is no need to think twice. If you take this course now, you will acquire invaluable skills that will help you stand out from the rest of the candidates competing for a job. Are you about to graduate from university and start looking for your first job? Are you a young professional who wants to establish themselves at their new position? Would you like to become your team’s go-to person when it comes to creating important PowerPoint presentations? If so, then this is the right course for you! It certainly pays off to be able to create great-looking PowerPoint presentations from scratch:
The instructor of the course has extensive experience with PowerPoint. His slides have been in front of some of the most influential executives in Europe. Learn how to organize your presentations in a professional manner, exactly like employees of Fortune100 companies do. Beginner to Pro in PowerPoint: Complete PowerPoint Training is THE ONLY course that will teach you how to prepare professional business presentations that are identical to the ones that are delivered by major investment banks and consulting firms. It’s a one-stop-shop for everything you need in order to create sophisticated presentations. In the first part of the course, we will cover PowerPoint’s basic tools. This makes the course appropriate for beginners and inexperienced users. Once we have done that, we will explore some advanced features, which are often neglected by average users. The third part of the course is a case study. We will go through the entire thought process that is necessary to create a well-structured company presentation. And then, we’ll create the actual presentation. You will gain first-hand experience on how to design great-looking PowerPoint slides! Get excited! This course is an opportunity to beat the learning curve and stand out from the crowd. Here’s what you get with Beginner to Pro in PowerPoint: Complete PowerPoint Training:
In addition to that you will receive:
By taking this course you will have every chance to:
Welcome to Credit Risk Modeling in Python. The only online course that teaches you how banks use data science modeling in Python to improve their performance and comply with regulatory requirements. This is the perfect course for you, if you are interested in a data science career. Here’s why: · The instructor is a proven expert (PhD from the Norwegian Business school, who has taught in world renowned universities such as HEC, the University of Texas, and the Norwegian Business school). · The course is suitable for beginners. We start with theory and initial data pre-processing and gradually solve a complete exercise in front of you · Everything we cover is up-to-date and relevant in today’s development of Python models for the banking industry · This is the only online course that shows the complete picture in credit risk in Python (using state of the art techniques to model all three aspects of the expected loss equation – PD, LGD, and EAD) including creating a scorecard from scratch · Here we show you how to create models that are compliant with Basel II and Basel III regulations that other courses rarely touch upon · We are not going to work with fake data.The dataset used in this course is an actual real-world example · You get to differentiate your data science portfolio by showing skills that are highly demanded in the job marketplace · What is most important – you get to see first-hand how a data science task is solved in the real-world Most data science courses cover several frameworks, but skip the pre-processing and theoretical part. This is like learning how to taste wine before being able to open a bottle of wine. We don’t do that. Our goal is to help you build a solid foundation. We want you to study the theory, learn how to pre-process data that does not necessarily come in the ‘’friendliest’’ format, and of course, only then we will show you how to build a state of the art model and how to evaluate its effectiveness. Throughout the course, we will cover several important data science techniques. – Weight of evidence – Information value – Fine classing – Coarse classing – Linear regression – Logistic regression – Area Under the Curve – Receiver Operating Characteristic Curve – Gini Coefficient – Kolmogorov-Smirnov – Assessing Population Stability – Maintaining a model Along with the video lessons you will receive several valuable resources that will help you learn as much as possible: · Lectures · Notebook files · Homework · Quiz questions · Slides · Downloads · Access to Q&A where you could reach out and contact the course tutor. The post List of the Best Data Science Courses on Udemy in 2020 appeared first on Data Science PR. via Data Visualization – Data Science PR https://ift.tt/38ZFBUJ
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Connection Maps are drawn by connecting points placed on a map by straight or curved lines.While Connection Maps are great for showing connections and relationships geographically, they can also be used to display map routes through a single chain of links. Connection Maps can also be useful in revealing spatial patterns through the distribution of connections or by how concentrated connections are on a map. The post What is Connection Map in Data Visualization? appeared first on Data Science PR. via Data Visualization – Data Science PR https://ift.tt/3ekbvfL A Density Plot visualises the distribution of data over a continuous interval or time period. This chart is a variation of a Histogram that uses kernel smoothing to plot values, allowing for smoother distributions by smoothing out the noise.The peaks of a Density Plot help display where values are concentrated over the interval. An advantage Density Plots have over Histograms is that they’re better at determining the distribution shape because they’re not affected by the number of bins used (each bar used in a typical histogram). A Histogram comprising of only 4 bins wouldn’t produce a distinguishable enough shape of distribution as a 20-bin Histogram would. However, with Density Plots, this isn’t an issue. The post Density Plot in Data Visualization appeared first on Data Science PR. via Data Visualization – Data Science PR https://ift.tt/2WaW3fW Circle Packing is a variation of a Treemap that uses circles instead of rectangles. Containment within each circle represents a level in the hierarchy: each branch of the tree is represented as a circle and its sub-branches are represented as circles inside of it. The area of each circle can also be used to represent an additional arbitrary value, such as quantity or file size. Colour may also be used to assign categories or to represent another variable via different shades. As beautiful as Circle Packing appears, it’s not as space-efficient as a Treemap, as there’s a lot of empty space within the circles. Despite this, Circle Packing actually reveals hierarchal structure better than a Treemap. The post What is Circle Packing in Data Visualization? appeared first on Data Science PR. via Data Visualization – Data Science PR https://ift.tt/2BSooAR Choropleth Maps display divided geographical areas or regions that are coloured, shaded or patterned in relation to a data variable. This provides a way to visualise values over a geographical area, which can show variation or patterns across the displayed location.The data variable uses colour progression to represent itself in each region of the map. Typically, this can be a blending from one colour to another, a single hue progression, transparent to opaque, light to dark or an entire colour spectrum. One downside to the use of colour is that you can’t accurately read or compare values from the map. Another issue is that larger regions appear more emphasised then smaller ones, so the viewer’s perception of the shaded values are affected. A common error when producing Choropleth Maps is to encode raw data values (such as population) rather than using normalized values (calculating population per square kilometre for example) to produce a density map. The post Data Visualization Explained: Choropleth Map appeared first on Data Science PR. via Data Visualization – Data Science PR https://ift.tt/2ZRyCt0 This type of diagram visualises the inter-relationships between entities. The connections between entities are used to display that they share something in common. This makes Chord Diagrams ideal for comparing the similarities within a dataset or between different groups of data. Nodes are arranged along a circle, with the relationships between points connected to each other either through the use of arcs or Bézier curves. Values are assigned to each connection, which is represented proportionally by the size of each arc. Colour can be used to group the data into different categories, which aids in making comparisons and distinguishing groups. Over-cluttering becomes an issue with Chord Diagrams when there are too many connections displayed. The post Data Visualization Explained: Chord Diagram appeared first on Data Science PR. via Data Visualization – Data Science PR https://ift.tt/38DhICu This type of chart is used as a trading tool to visualise and analyse the price movements over time for securities, derivatives, currencies, stocks, bonds, commodities, etc. Although the symbols used in Candlestick Charts resemble a Box Plot, they function differently and therefore, are not to be confused with one another.Candlestick Charts display multiple bits of price information such as the open price, close price, highest price and lowest price through the use of candlestick-like symbols. Each symbol represents the compressed trading activity for a single time period (a minute, hour, day, month, etc). Each Candlestick symbol is plotted along a time scale on the x-axis, to show the trading activity over time. The main rectangle in the symbol is known as the real body, which is used to display the range between the open and close price of that time period. While the lines extending from the bottom and top of the real body is known as the lower and upper shadows (or wick). Each shadow represents the highest or lowest price traded during the time period represented. When the market is Bullish (the closing price is higher than it opened), then the body is coloured typically white or green. But when the market is Bearish (the closing price is lower than it opened), then the body is usually coloured either black or red. Candlestick Charts are great for detecting and predicting market trends over time and are useful for interpreting the day-to-day sentiment of the market, through each candlestick symbol’s colouring and shape. For example, the longer the body is, the more intense the selling or buying pressure is. While, a very short body, would indicate that there is very little price movement in that time period and represents consolidation. Candlestick Charts help reveal the market psychology (the fear and greed experienced by sellers and buyers) through the various indicators, such as shape and colour, but also by the many identifiable patterns that can be found in Candlestick Charts. In total, there are 42 recognised patterns that are divided into simple and complex patterns. These patterns found in Candlestick Charts are useful for displaying price relationships and can be used for predicting the possible future movement of the market. You can find a list and description of each pattern here. Please bear in mind, that Candlestick Charts don’t express the events taking place between the open and close price – only the relationship between the two prices. So you can’t tell how volatile trading was within that single time period. 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