2 Educators providing Pandas courses in London

Basic Python syntax and principles of Object Orientated Programming. Most attendees are in-work IT Professional. Private individuals are also very welcome. Evening courses also running. Our Style: Hands-on, Practical Location: Online, Instructor-led Download: anaconda.com Duration: 6 weeks, 1 evening per week, 6pm - 8pm Times: arrange a time for your time zone

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

PYTHON BOOTCAMP: This 12-week Python Data Analytics Data Boot Camp is designed to give you a complete skill set required by data analysts . You will be fully fluent and confident as a Python data analyst, with full understanding of Python Programming. From Data, databases, datasets, importing, cleaning, transforming, analysing to visualisation and creating awesome dashboards The course is a practical, instructor-lead program.

Learn to code Python, from scratch to job-ready. With this excellent Python Programming course London you will achieve job-ready coding expertees. How does it work? Online, Instructor-led lessons: 1 full day lesson per week, for 12 weeks Plus Self-study Materials and a Structured Self-Study Program Plus 1-1 mentoring Scheduled in addition Plus Live Online Practical Project to showcase your expertees Part Time Part Time 1 full day per week, online instructor-led. Self study, in your own time. 1-1 mentoring, schedule your preferred time. Earn and Learn, stay employed, work, earn your salary until you qualify, then change. 1-1 Mentoring 1-1 Mentoring Additional, between weekly sessions. Work at your pace, 1-1 sessions can cover extra work and/or help you catch up. Gain confidence, because we revise & validate your practicals. Be re-assured, get immediate answers to your questions. Self-Study Self-Study Learn by doing, the best way to re-inforce learning, is by trying on your own. Practical, most of the self-study work is practical exercises. Gain experience, this aspect of the course gives you experience employesr are seeking. Practical Project Practical Project Live online, upload your project. Showcase, your expertees are testified online. Become known, your project will put you in contact with the coding community. Materials Materials Video Tutorials, Short and easy. Python Coding Examples, Plenty thereof. Manuals and Notes Reference materials. Exercises, Practical work with every class. Payments Payments Best deal: → £2100 up front. Installments: Contact us to arrange. Our Style Our Style Personalised, 1-1 Mentoring & Small Groups, Max 4. Practical, Hand-on. Online Instructor-Led. Weekly topics and other details Weekly Python lesson topic descriptions Overview of Python Fundamentals: Python Data Types, Variables: Primitive types; Characters; Boolean; Working with variables and its scope; Type conversion and casting; Strings String Functions, Strings vs numbers vs dates. Getting user input. Python Operators and Expressions: Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators. Decision Making: If statement; If - else statement; If- else if - else statement; Nested if - else; Switch Statements Using Loops: The while, do-while and the for loop; Enhanced for loop; Jump statements : break, continue; The return statement; Nesting loops. OOP Principals Using Methods: Learn Python method basics. Defining Methods, Parameters, Returning values, Overloading methods, Calling methods. Encapsulation. Classes and Objects Inheritance, Override, Constructors, Parametised Constructors, the self keyword, Inner classes Lists. Tuples. Sets, Dictionary. Json Files. Using Built-in modules and functions for strings, maths and dates. Exception Handling, Files, Streams. Database concepts, Relational Database Data Types, Columns, Tables Relationships SQL statements DDL SQL Statements: Create and drop a databases Create,aleter and drop alter tables Select queries: where-clauses, wildcards, order by, joins, aggregates, having, DML Queries: Insert, Update and deleting records Connect to a from Python to a SQLite3 database, Data Driven Python Project: DDL Queries: Create a table, alter tables, drop a table Creating a log of transactions, using the above DML Queries: insert, delete, update records Creating a log-in facility to register, delete and maintain users Create a Search facility using select queries Query a database with wildcard parameters and display results Numpy Arrays The Python NumPy Module: Working with arrays, create data using arrays. Array manipulation and array-wise math functions. String functions on arrays. Numpy Built-In Functions : Math, arithmetic and statistical functions. Numpy Calculations Pandas Series Data Cleaning Python Pandas Dataframes and data importing Python Dataframes Data Series. Date/ Time Functionality. Time series. Creating Dataframes, Indexing. Dict to Dataframe, Dataframe to Dict. Csv to Dataframe, Dataframe to csv. Excel to Dataframe, Dataframe to Excel. Data Cleaning and preparation Finding, replacing and filtering missing data. Remove Duplicates. Replacing values. Renaming Axis Indexes. Pandas Data Wrangling Discretization and Binning. Random Sampling. Transforing data using function and mapping, Hierarchical Indexing, Reorder, Sorting, Stastitics, Dataframe Joins, Merging, Concatenation, Overlap. Reshaping and pivoting. Query a Pandas Dataframe Data Analysis: Sorting. Analysing and finding data using filter, slicing and dataframe queries. Finding data by Iteration. Find statistics: Functions, Aggregate functions. Unique values. String objects, Regex. Chart Types: Bar, Column, Line, Scatter, Pie, Area, Histogram, Funnel Charts Formatting: Changing gridlines lines, axes, scales, markers, colours, Chart Elements: legends, titles, plot seizes, exporting. Supervised Machine Learning: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine Regression Algorithms: Linear, Polynomial Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) Association Algorithms: Apriori, Euclat Ensemble Methods Algorithms: Stacking, bagging, boosting. Random Forest Random Forest, Gradient Boosting Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN) Data Exploration and Preprocessing: Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. Python Tkinter Front-end Basics Getting Started with HTML Getting Started with CSS Getting Started with Php Getting Started with JavaScripts Book the Python Boot Camp About us Our experienced trainers are award winners. More about us FAQ's Client Comments

Python Basics: Course Description Excellent for beginners, practical, in small groups of max 4 people, 1 Day Online Instructor-led. You could contact us for your prefereed date. Session 1: Python Data Types and Variables: Primitive types; Characters & Strings; Boolean; Working with variables and its scope; Conversion and casting types in Python. Operators and Expressions: Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators.. Exercise: Calculate Movie Tickets for a Party, Are there enough seats in the cinema? Decision Making & Loops If statement; If - else statement; If- elif - else statement; Nested if - else; Exercise: Calculate the travel fee to deliver goods The while, For loop Jump statements: break, continue; Nesting loops. Exercise: Enter a password, if incorrect 3 times, you are blocked. Session 2: Data Structures Lists. Tuples. Exercise: Hangman Game Exercise: Get a word for the game from a Json File, store the high score in a Dictionary file Session 3: Files and exceptions Exception Handling, Exception types; Using try and Except. Files, streams: Open, Traverse, Read and Create Files: Csv, txt and Json Files. API: Connecting to API’s. Session 4: OOP Creating and using custom Functions. Using parameters and return values. Creating a Class; Creating an Object; Using an Object; Adding Instance variables; Class Constructors; Parameterized Constructors. Inheritance. Override. Session 5: Pandas Dataframe Basics Getting data into a dataframe: Dict to Dataframe, Dataframe to Dict. Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets. Getting information about the dataframe, Filter, sort and query a Dataframes, Slicing Dataframes, Duplicate values,Working with null-values, Sampling. Exercise: Query the top 1000 grossing movies of the last century Session 6: Built in Functions: String, Math, Random Python built-in functions: Strings functions. Maths functions. Random Functions. Exercise: Find information in prose, to get the sentiment of the prose. Exercise: Get a word for the game from a txt File Exercise: Win the lottery Included: PCWorkshops's Python Programming Basics Certification Course notes, exercises and code examples Revision session after the course Refund Policy No Refunds

his course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. These concepts are daily used by programmers and is your first step to working as a programmer. By the end, you'll be comfortable in programming Python code. You will have done small projects. This will serve for you as examples and samples that you can use to build larger projects.

This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.

Maximize the value of data assets in the oil and gas sector with EnergyEdge's assessment-based training course on Python programming and analytics.