Data Science - Education, Online Learning
Machine Learning Bootcamp: Hand-On Python in Data Science
Maths for Data Science by DataTrained
Power BI A-Z: Hands-On Power BI Training For Data Science!
Data Science For Product Managers 2023 Bootcamp
Blog
-
Beauty
Beauty Lotions -
Health & Personal Care
Weight Management -
Education
Machine Learning Bootcamp: Hand-On Python in Data Science
About Development, Data Science
This course focuses on one of the main branches of Machine Learning that is Supervised Learning in Python. If you are not familiar with Python, there is nothing to worry about because the Lectures comprising the Python Libraries will train you enough and will make you comfortable with the programming language.The course is divided into two sections, in the first section, you will be having lectures about Python and the fundamental libraries like Numpy, Pandas, Seaborn, Scikit-Learn and Tensorflow that are necessary for one to be familiar with before putting his hands-on Supervised Machine Learning.Then is the Supervised Learning part, which basically comprises three main chapters Regression, Classification, and Deep Learning, each chapter is thoroughly explained, both theoretically and experimentally.During all of these lectures, we'll be learning how to use the different machine learning algorithms to create some mind-blowing modules of Machine Learning, and at the end of the course, you'll be trained enough that you would be able to develop you own Recognitions Systems and Prediction Models and many more.Let's get started!
Maths for Data Science by DataTrained
About Development, Data Science
Overview: Explore the application of key mathematical topics related to linear algebra with the Python programming language.Expected Duration: After completion of this course, you should be able to accomplish the objectives from the following lessons and topics. 1. Lessons on Math for Data Science & Machine Learning: 2. Understand how to work with vectors in Python3. Basis and Projection of Vectors: Understand the Basis and Projection of Vectors in Python4. Work with Matrices: Understand how to work with matrices in Python5. Matrix Multiplication: Understand how to multiply matrices in Python6. Matrix Division: Understand how to divide matrices in Python7. Linear Transformations: Understand how to work with linear transformations in Python8. Gaussian Elimination: Understand how to apply Gaussian Elimination9. Determinants: Understand how to work with determinants in Python10. Orthogonal Matrices: Understand how to work with orthogonal matrices in Python11. Eigenvalues: Recognize how to obtain eigenvalues from eight decompositions in Python12. Eigenvectors: Recognize how to obtain eigenvectors from eigendecomposition in Python13. PseudoInverse: Recognize how to obtain pseudoinverse in Python
Power BI A-Z: Hands-On Power BI Training For Data Science!
About Business, Business Analytics Intelligence
Learn data visualization through Microsoft Power BI and create opportunities for you or key decision makers to discover data patterns such as customer purchase behavior, sales trends, or production bottlenecks. You'll learn all of the features in Power BI that allow you to explore, experiment with, fix, prepare, and present data easily, quickly, and beautifully. Use Power BI to Analyze and Visualize Data So You Can Respond Accordingly Connect Power BI to a Variety of Datasets Drill Down and Up in Your Visualization and Calculate Data Visualize Data in the Form of Various Charts, Plots, and Maps Convert Raw Data Into Compelling Data Visualizations Using Power BI Because every module of this course is independent, you can start in whatever section you wish, and you can do as much or as little as you like. Each section provides a new data set and exercises that will challenge you so you can learn by immediately applying what you're learning. Content is updated as new versions of Power BI are released. You can always return to the course to further hone your skills, while you stay ahead of the competition. Contents and Overview This course begins with Power BI basics. You will navigate the software, connect it to a data file, and export a worksheet, so even beginners will feel completely at ease. To be able to find trends in your data and make accurate forecasts, you'll learn how to work with hierarchies and timeseries. Also, to make data easier to digest, you'll tackle how to use aggregations to summarize information. You will also use granularity to ensure accurate calculations. In order to begin visualizing data, you'll cover how to create various charts, maps, scatterplots, and interactive dashboards for each of your projects. You'll even learn how to join multiple data sources into one in order to combine diverse sources of information in one analytical solution. Finally, you'll cover some of the latest and most advanced custom visualizations in Microsoft Power BI, where you will create histograms, brickcharts and more. By the time you complete this course, you'll be a highly proficient Power BI user. You will be using your skills as a data scientist to extract knowledge from data so you can analyze and visualize complex questions with ease. You'll be fully prepared to collect, examine, and present data for any purpose, whether you're working with scientific data or you want to make forecasts about buying trends to increase profits.
Data Science For Product Managers 2023 Bootcamp
About Business, Business Analytics Intelligence
DATA SCIENCE FOR PRODUCT MANAGERSBecome Data Driven Product ManagerWhat will you Learn?Demonstrate a fundamental understanding of end to end aspects of Data Science and ability to interlock with Management team and Data Scientist team.Types of Data Science Models & Algorithms commonly used in the industry along with is business applicationsBe able to work effectively with data science teams to build great products & services.Ability to jumpstart a career as a Data Smart Manager.Top skills you will learnData Analysis to Drive Decision Making, Analysis Methods - Descriptive Analysis, Predictive Analysis, Prescriptive Analysis. Big Data Terminologies, Data Science Algorithms and its applications (ex. Component Analysis, K-Means Clustering, Association Rules, Regression Analysis, K-Nearest Neighbors, Decision Trees etc.). Unsupervised Learning, Data Visualization, Data Story Telling, Data Monetization. Setting up and Managing Data Teams and more..Ideal ForBusiness Professionals like Business Analysts, Project Managers, Program Managers.Technology Professionals like - Q/A, Engineering Leads, Solutions Architect, Software Developers. Customer Facing Professionals like - Marketing Analysts, Sales, Entrepreneurs, Delivery Managers, Functional Managers.Anyone who wants to build and end to end understanding and orientation of the world of Data Science and how to drive Data Science projects & Data Driven business decisions.NO prior knowledge of Data Science, Programming or Statistics required.
