Welcome to Data Analysis Analytics Bootcamp content powered by TakenMind. Are you interested to learn how zetabytes of data are processed by top tech companies to analyse data inorder to boost their business growth? Well, for a beginner you are at the right place and this is the most probably the right time for you to learn this. The average data scientist today earns $123,000 a year, according to Indeed research. But the operating term here is “today,” since data science has paid increasing dividends since it really burst into business consciousness in recent years. This course has its base on financial Analysis and the following concepts are covered: Python Fundamentals Pandas for Efficient Data Analysis NumPy for High Speed Numerical Processing Matplotlib for Data Visualization Pandas for Data Manipulation and Analysis Seaborn Data Visualization Worked-up examples. Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more! You will learn how to: Import data sets Clean and prepare data for analysis Manipulate pandas DataFrame Summarize data Build machine learning models using scikit-learn Build data pipelines Data Analysis with Python is delivered through lecture, hands-on labs, and assignments. It includes following parts: Data Analysis libraries: will learn to use Pandas DataFrames, Numpy multi-dimentional arrays, and SciPy libraries to work with a various datasets. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions.

If you want to learn simple, effective techniques to create impactful Excel Dashboards and Data Analysis, this course is ideal. Updated in 2021 with full high definition video , this course teaches you practical skills you can apply in your work environment immediately. Just take a look at the recent comments and reviews! "Presentation is great! Very practical solutions for everyday business analysis challenges." "I walked away with a lot much practical knowledge. Really excited to apply this knowledge in my work. I have taken other courses from Ian and never disappointed." "One of the best courses I have taken on Udemy!!! Very easy to understand, not long and drawn out and focuses on what is relevant in the work place. Will definitely recommend it to my team." "Really enjoyed the course, so many practical tips, which are easily explained. Thanks" In this course, you will learn the BEST techniques and tools for turning data into MEANINGFUL analysis using Excel This course is lead by Ian Littlejohn - an international trainer, consultant and data analyst with over 125 000 enrollments & 100 000 students on Udemy. Ian specializes in teaching data analysis techniques, Excel Pivot Tables, Power Pivot, Microsoft Power BI, Google Data Studio & Amazon Quicksight & his courses average over 4.5 stars out of 5. **** Life-time access to course materials and practice activities.  **** The Complete Introduction to Business Data Analysis teaches you how to apply different methods of data analysis to turn your data into new insight and intelligence . The ability to ask questions of your data is a powerful competitive advantage , resulting in new income streams, better decision making and improved productivity.  A recent McKinsey Consulting report has identified that data analysis is one of the most important skills required in the American economy at the current time. During the course you will understand why the form of analysis is important and also provide examples of analysis using Excel. The following methods of analysis are included: Key Metrics Comparison Analysis Trend Analysis Ranking Analysis Interactive Dashboards Contribution Analysis Variance Analysis Pareto Analysis Frequency Analysis Correlations The Complete Introduction to Business Data Analysis is designed for all business professionals who want to take their ability to turn data into information to the next level . If you are an Excel user then you will want to learn the easy-to-use techniques that are taught in this course. This course is presented using Excel in Office 365.  However, the course is also suitable for: Excel 2013 Excel 2016 Excel 2019 Please note that this course does not include any complicated formulas, VBA or macros.  The course utilizes drag and drop techniques to create the majority of the different data analysis techniques.

Data analysis becomes essential part of every day life. After this course, you will be able to conduct data analysis task yourself. Gain insights from the data. Will be using R - widely used tool for data analysis and visualization. Data Science project will be core course component - will be working on it after mastering all necessary background. Doing data analysis from ground up to final insights. Starting from very basics we will move to various input and output methods. Yet another important concept - visualization capabilities. After the course you will be able to produce convincing graphs. Background behind functional programming will be presented - including building your own functions. After finishing the course you will feel much more comfortable programming in other languages as well. This is because R being fully empowered programming language itself. Main programming concepts presented: Various data types Conditional statements For and While loops No previous programming knowledge required. Finally, data mining and data science techniques in R delivered in clear fashion together with assignments to make sure you understand topics. Main statistical capabilities behind data science covered. Course is interactive . Specific topic covered in each lecture. Each lecture includes multiple examples. All material covered in videos are available for download! This way student is able to program himself - break things and fix them. Students will finish course in approximately 7-10 days working 3 hours per day. Time spent working individually included. After each section assignment should be completed to make sure you understand material in the section. After you are ready with the solution - watch video explaining concepts behind assignment. I will be ready to give you a hand by answering your questions. Finally, this course is specifically designed to get up to speed fast. Biggest emphasis put on real examples and programming yourself. This distinguishes this course from other material available online - usual courses includes vague slides and long textbooks with no real practise.

Are you ready to kickstart your career in Data Analytics ? Need more knowledge in Tableau, Data Visualization and Analytics? This course is for YOU. In this course you will build 5 separate dashboards depicting real world problems. You will learn how to connect to various data sources from Excel files to cloud servers. You will also learn how to build interactive dashboards and publish it to Tableau Online! You will master the skills to become a good Data Analyst and build a solid foundation in understanding the data pipeline. In this course you will learn: Create 5 interactive dashboards and publish it online to share Learn how to connect to different data sources such as Excel, Google Sheets and Cloud Servers. Create a variety of charts including bar charts, line charts, donut charts, maps, tables and dual axis charts. Create calculated fields including developing IF Statements. Create sets, hierarchies and groups. Understanding how joins work. Understand Level Of Detail calculations. Create Parameters Make use of the analytics pane including using trend lines How to use dashboard actions and create interactive dashboards. Creating a dashboard which updates daily via google sheets. By the time you complete this course, you'll be a highly proficient Tableau user and use all the learning from to course to enhance your career in Data and Analytics. Projects you will work on: Discount Mart: Discount Mart is a small supermarket.The owner wants a dashboard where he can track how well Discount Mart is doing for this year (in terms of Sales, Profit and Quantity Sold). Green Destinations: Green Destinations is a well known travel agency. The HR Director has recently noticed an increase in employees leaving (attrition). She would like to figure out any trends or patterns based on a dashboard we will be building for her. Super Store: Superstore is a famous retailer in Canada. They have expanded into the USA and their business model involves placing Sales Agents in every state in the USA. These sales agents are responsible for bringing in sales for the state that they are assigned. The Sales Manager wants a dashboard to track how Sales Agents are doing. Northwind Trade: Northwind Trade is a company which ships a variety of FMCG (Fast Moving Consumer Goods) all over the world. The Shipping Manager doesn't have much visibility and doesn't know how many orders are processed and shipped on a monthly basis. He would like a dashboard of this where he selects a month and can tell how many orders are outstanding a day and where they should be shipped. Tesla: Tesla is an American electric vehicle and clean energy company. An important shareholder is tired of receiving only monthly updates of the stock price. The shareholder would like to see any trends of the stock price specifically for the last 3 months. He also wants this data to be updated daily.

Student Testimonials: The instructor knows the material, and has detailed explanation on every topic he discusses. Has clarity too, and warns students of potential pitfalls. He has a very logical explanation, and it is easy to follow him. I highly recommend this class, and would look into taking a new class from him. - Diana This is excellent, and I cannot complement the instructor enough. Extremely clear, relevant, and high quality - with helpful practical tips and advice. Would recommend this to anyone wanting to learn pandas. Lessons are well constructed. I'm actually surprised at how well done this is. I don't give many 5 stars, but this has earned it so far. - Michael This course is very thorough, clear, and well thought out. This is the best Udemy course I have taken thus far. (This is my third course.) The instruction is excellent! - James Welcome to the most comprehensive Pandas course available on Udemy! An excellent choice for both beginners and experts looking to expand their knowledge on one of the most popular Python libraries in the world! Data Analysis with Pandas and Python offers 19+ hours of in-depth video tutorials on the most powerful data analysis toolkit available today. Lessons include: installing sorting filtering grouping aggregating de-duplicating pivoting munging deleting merging visualizing and more! Why learn pandas? If you've spent time in a spreadsheet software like Microsoft Excel, Apple Numbers, or Google Sheets and are eager to take your data analysis skills to the next level, this course is for you! Data Analysis with Pandas and Python introduces you to the popular Pandas library built on top of the Python programming language. Pandas is a powerhouse tool that allows you to do anything and everything with colossal data sets -- analyzing, organizing, sorting, filtering, pivoting, aggregating, munging, cleaning, calculating, and more! I call it "Excel on steroids"! Over the course of more than 19 hours, I'll take you step-by-step through Pandas, from installation to visualization! We'll cover hundreds of different methods, attributes, features, and functionalities packed away inside this awesome library. We'll dive into tons of different datasets, short and long, broken and pristine, to demonstrate the incredible versatility and efficiency of this package. Data Analysis with Pandas and Python is bundled with dozens of datasets for you to use. Dive right in and follow along with my lessons to see how easy it is to get started with pandas! Whether you're a new data analyst or have spent years (*cough* too long *cough*) in Excel, Data Analysis with pandas and Python offers you an incredible introduction to one of the most powerful data toolkits available today!

Please note that, We have divided the "Econometrics" course in to TWO parts as follows: Econometrics#1:  Regression Modeling, Statistics with EViews Econometrics#2: Econometrics Modeling and Analysis in EViews This is the Second part and will cover Multivariate Modeling, Autocorrelation Techniques, VAR Modeling, Stationarity and Unit Root Testing, CoIntegration Testing and Volatility & ARCH Modeling. This course aims to provide basic to intermediate skills on implementing Econometrics/Predictive modelling concepts using Eviews software. Whilst its important to develop understanding of econometrics/quantitative modelling concepts, its equally important to be able to implement it using suitable software packages. This course fills the gap between understanding the concepts and implementing them practically. The course works across multiple software packages such as Eviews, MS Office, PDF writers, and Paint. Econometric modeling course aims to provide quantitative/econometric modelling skills typically/specifically in Finance sector. Quantitative methods and predictive modelling concepts could be extensively used in understanding the financial markets movements, and studying tests and effects. The course picks theoretical and practical datasets for econometrics/quantitative/predictive analysis. Implementations are done using Eviews software. Observations, interpretations, predictions and conclusions are explained then and there on the examples as we proceed through the training. The course also emphasizes on the regression models, and AIMS to also cover Auto-Correlation, Co-Integration and ARCH (Auto Regressive Conditional Heteroscedasticity) models.  Essential skillsets – Prior knowledge of Quantitative methods and MS Office, Paint  Desired skillsets — Understanding of Data Analysis and VBA toolpack in MS Excel will be useful The course works across multiple software packages such as Eviews, MS Office, PDF writers, and Paint.

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. 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. For example, one would struggle in the application of Machine Learning techniques before understanding the underlying Mathematics. Or, it can be overwhelming to study regression analysis in Python before knowing what a regression is. So, in an effort to create the most effective, time-efficient, and structured data science training available online, we created The Data Science Course 2021. We believe this is the first training program that solves the biggest challenge to entering the data science field – having all the necessary resources in one place. Moreover, our focus is to teach topics that flow smoothly and complement each other. The course teaches you everything you need to know to become a data scientist at a fraction of the cost of traditional programs (not to mention the amount of time you will save). The Skills 1. Intro to Data and Data Science Big data, business intelligence, business analytics, machine learning and artificial intelligence. We know these buzzwords belong to the field of data science but what do they all mean? Why learn it? As a candidate data scientist, you must understand the ins and outs of each of these areas and recognise the appropriate approach to solving a problem. This ‘Intro to data and data science’ will give you a comprehensive look at all these buzzwords and where they fit in the realm of data science. 2. Mathematics Learning the tools is the first step to doing data science. You must first see the big picture to then examine the parts in detail. We take a detailed look specifically at calculus and linear algebra as they are the subfields data science relies on. Why learn it? Calculus and linear algebra are essential for programming in data science. If you want to understand advanced machine learning algorithms, then you need these skills in your arsenal. 3. Statistics You need to think like a scientist before you can become a scientist. Statistics trains your mind to frame problems as hypotheses and gives you techniques to test these hypotheses, just like a scientist. Why learn it? This course doesn’t just give you the tools you need but teaches you how to use them. Statistics trains you to think like a scientist. 4. Python Python is a relatively new programming language and, unlike R, it is a general-purpose programming language. You can do anything with it! Web applications, computer games and data science are among many of its capabilities. That’s why, in a short space of time, it has managed to disrupt many disciplines. Extremely powerful libraries have been developed to enable data manipulation, transformation, and visualisation. Where Python really shines however, is when it deals with machine and deep learning. Why learn it? When it comes to developing, implementing, and deploying machine learning models through powerful frameworks such as scikit-learn, TensorFlow, etc, Python is a must have programming language. 5. Tableau Data scientists don’t just need to deal with data and solve data driven problems. They also need to convince company executives of the right decisions to make. These executives may not be well versed in data science, so the data scientist must but be able to present and visualise the data’s story in a way they will understand. That’s where Tableau comes in – and we will help you become an expert story teller using the leading visualisation software in business intelligence and data science. Why learn it? A data scientist relies on business intelligence tools like Tableau to communicate complex results to non-technical decision makers. 6. Advanced Statistics Regressions, clustering, and factor analysis are all disciplines that were invented before machine learning. However, now these statistical methods are all performed through machine learning to provide predictions with unparalleled accuracy. This section will look at these techniques in detail. Why learn it? Data science is all about predictive modelling and you can become an expert in these methods through this ‘advance statistics’ section. 7. Machine Learning The final part of the program and what every section has been leading up to is deep learning. Being able to employ machine and deep learning in their work is what often separates a data scientist from a data analyst. This section covers all common machine learning techniques and deep learning methods with TensorFlow. Why learn it? Machine learning is everywhere. Companies like Facebook, Google, and Amazon have been using machines that can learn on their own for years. Now is the time for you to control the machines. ***What you get*** A $1250 data science training program Active Q&A support All the knowledge to get hired as a data scientist A community of data science learners A certificate of completion Access to future updates Solve real-life business cases that will get you the job You will become a data scientist from scratch We are happy to offer an unconditional 30-day money back in full guarantee. No risk for you. The content of the course is excellent, and this is a no-brainer for us, as we are certain you will love it. Why wait? Every day is a missed opportunity. Click the “Buy Now” button and become a part of our data scientist program today.

PLEASE READ BEFORE ENROLLING: 1.) THERE IS AN UPDATED VERSION OF THIS COURSE: "PYTHON FOR DATA SCIENCE AND MACHINE LEARNING BOOTCAMP" 2.) IF YOU ARE A COMPLETE BEGINNER IN PYTHON-CHECK OUT MY OTHER COURSE "COMPLETE PYTHON MASTERCLASS JOURNEY"! CLICK ON MY PROFILE TO FIND IT. (PLEASE WATCH THE FIRST PROMO VIDEO ON THIS PAGE FOR MORE INFO) ********************************************************************************************************** This course will give you the resources to learn python and effectively use it analyze and visualize data! Start your career in Data Science! You'll get a full understanding of how to program with Python and how to use it in conjunction with scientific computing modules and libraries to analyze data. You will also get lifetime access to over 100 example python code notebooks, new and updated videos, as well as future additions of various data analysis projects that you can use for a portfolio to show future employers! By the end of this course you will: - Have an understanding of how to program in Python. - Know how to create and manipulate arrays using numpy and Python. - Know how to use pandas to create and analyze data sets. - Know how to use matplotlib and seaborn libraries to create beautiful data visualization. - Have an amazing portfolio of example python data analysis projects! - Have an understanding of Machine Learning and SciKit Learn! With 100+ lectures and over 20 hours of information and more than 100 example python code notebooks, you will be excellently prepared for a future in data science!

This is an introductory course designed to help business professionals and others learn predictive analytic skills that can be applied in a business setting. Since it is designed for business professionals it doesn't delve too deeply into the mathematics of the statistical models. We do the following case studies on Rapidminer software: B2B Churn of an office supply distributor, Market Basket Analysis of a retail computer store, Customer Segmentation of a customer database and Direct Marketing. The following models are used: Linear Regression, Logistic Regression, Association Rules, K-means Clustering and Decision Trees. Through these practical case studies we generate actionable business insights!

Data analysis is critical in business. Get ahead in your career with this important skill. Management depends on decision making and problem solving.   They depend on analytical findings. Not only do we need good sources of data, but we need skills that allow us to interpret and report the results. Discover techniques and best practices for analysis by learning the analytical process.