126 Courses in Bristol delivered Live Online

Get job ready with CompTIA's Data Analysis Certification. Live Classes - Career Guidance - Exam Included.

This course is designed for students who already have foundational knowledge and skills in Excel and who wish to perform robust and advanced data and statistical analysis with Microsoft Excel using PivotTables, use tools such as Power Pivot and the Data Analysis ToolPak to analyze data and visualize data and insights using advanced visualizations in charts and dashboards in Excel.

Duration 2 Days 12 CPD hours This course is intended for This course is designed for students who already have foundational knowledge and skills in Excel and who wish to perform robust and advanced data and statistical analysis with Microsoft Excel using PivotTables, use tools such as Power Pivot and the Data Analysis ToolPak to analyze data, and visualize data and insights using advanced visualizations in charts and dashboards in Excel. To ensure success, you should have baseline skill using Microsoft Excel worksheets, particularly in creating workbooks with formulas and function Overview #NAME? Analyzing data to find issues, insights and opportunities, is now a critical part of many job roles. Beyond the analysis, data analysts in all job roles must be able to effectively present and communicate their findings in visually compelling ways. Microsoft© Excel© is designed for this purpose. Excel can connect to a wide range of data sources, perform robust data analysis and create diverse and robust data-backed visualizations to show insights, trends, and create reports. These capabilities enable people who use Excel for data analysis to turn data into thoughtful action. 1 - DATA ANALYSIS FUNDAMENTALS Introduction to Data Science Create and Modify Tables Sort and Filter Data 2 - VISUALIZING DATA WITH EXCEL Visualize Data with Charts Modify and Format Charts Apply Best Practices in Chart Design 3 - ANALYZING DATA WITH FORMULAS AND FUNCTIONS Analyze Data with Formulas and Named Ranges Analyze Data with Functions Implement Data Validation, Forms, and Controls Create Conditional Visualizations with Lookup Functions 4 - ANALYZING DATA WITH PIVOTTABLES Create a PivotTable Analyze PivotTable Data 5 - PRESENTING VISUAL INSIGHTS WITH DASHBOARDS IN EXCEL Visualize Data with PivotCharts Filter Data Using Slicers and Timelines Create a Dashboard in Excel 6 - CREATING GEOSPATIAL VISUALIZATIONS WITH EXCEL Create Map Charts in Excel Customize Map Charts in Excel 7 - PERFORMING STATISTICAL ANALYSIS Visualize Trendlines and Sparklines with Excel Analyze Data with the Data Analysis ToolPa 8 - GETTING AND TRANSFORMING DATA Connect to Data with Queries Clean and Combine Data Shape and Transform Data 9 - MODELING AND ANALYZING DATA WITH POWER PIVOT Install Power Pivot in Excel Create Data Models with Power Pivot Create Power Pivots Perform Advanced Data Analysis and Visualization 10 - PRESENTING INSIGHTS WITH REPORTS (OPTIONAL) Plan a Report Create a Report

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Expand your Excel knowledge and learn how to structure and analyse large data sets.

Whetstone Communications and comms2point0 are pleased to bring you the Data Bites series of free webinars. Our aim is to boost interest and levels of data literacy among not-for-profit communicators.

The Real Estate Analyst course has been taught non-stop to global real estate firms over the last 25 years, and is without doubt the core financial modelling training in your career portfolio. Whether you have an upcoming financial modelling test for a new job or an APC exam, the Real Estate Analyst course is the choice for you.

Overview Data and visual analytics are emerging fields concerned with analysing, modelling, and visualizing complex high-dimensional data. It can be analysed and visualised with many languages like Python, R Programming and more. This course will help to attain the skills and give in-depth knowledge to the participant's enhanced way of modelling, analysing and visualizing techniques.  The course will highlight practical challenges including composite real-world data and will also comprise several practical studies

Learn advanced concepts in DAX, Data Modeling, Power BI architectural design, and more.

Python Data Analytics with Python using Numpy, Pandas, Dataframes. Most attendees are in-work Data Professional. Private individuals are very welcome. Our Style: Hands-on, Practical Location: Online, Instructor-led