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Online Coding Course (Complete Coding Training)

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Online Coding Course (Complete Coding Training)

"Online Coding Course (Complete Coding Training)" Do you want to learn coding, Are you searching for online coding course, online coding class, learn coding online or online programming course. Do you want to become a professional in coding. If yes, Indigenous i.t solution training institute (Online Training Ng) has brought an intensive course /training to learn coding online at the comfort of your home or office. This is a complete Professional 9 in 1 courses and training program that cover everything you need to know about coding and things you can't learn anywhere about coding. In this powerful training program, you will learn -:

  • How To Get Started with Coding
  • Career Building with Coding 
  • Basic Web Coding
  • Advanced Web Coding
  • Creating Web Applications
  • Selecting Data Analysis Tools
  • Evaluating Data
  • Essentials of Machine Learning
  • Applying Machine Learning

And many more, this course/training program contain everything you need to know to kick-start your career in coding. The ability to read, write, and understand code has never been more important, useful, or lucrative than it is today. Computer code has forever changed our lives. Many people can’t even make it through the day without interacting with something built with code. Even so, for many people, the world of coding seems complex and inaccessible. Maybe you participated in a tech-related business meeting and did not fully understand the conversation. Perhaps you tried to build a web page for your family and friends, but ran into problems displaying pictures or aligning text. Maybe you’re even intimidated by the unrecognizable words about coding, words such as HTML, CSS, JavaScript, Python, or Ruby. If you’ve previously been in these situations, then our Coding course/training is for you. This course/training explains basic concepts so you can participate in technical conversations and ask the right questions, and it goes even further than Coding For Beginners by covering additional topics in data science, machine learning, and coding careers. Don’t worry — this course/training assumes you’re starting with little to no previous coding knowledge, and I haven’t tried to cram every possible coding concept into these courses. Additionally, I encourage you here to learn by doing and by actually creating your own programs. Instead of a website, imagine that you want to build a house. You could spend eight years studying to be an architect, or you could start today by learning a little bit about foundations and framing. This course/training kick-starts your coding journey today. The importance of coding is ever-increasing. As author and technologist Douglas Rushkoff famously said, “program or be programmed.” When humans invented languages and then the alphabet, people learned to listen and speak, and then read and write. In our increasingly digital world, it’s important to learn not just how to use programs but also how to make them. For example, observe this transition in music. For over a century, music labels decided what songs the public could listen to and purchase. In 2005, three coders created YouTube, which allowed anyone to release songs. Today more songs have been uploaded to YouTube than have been released by all the record labels combined in the past century.

About This Course/Training

This course/training is designed for people with little to no coding experience, and gives an overview of programming to non-programmers. In plain English, you learn how code is used to create web programs, who makes those programs, and the processes they use. The lessons and topics covered include

  • Explaining what coding is and answering the common questions related to code
  • Building basic websites using the three most common languages: HTML, CSS, and JavaScript
  • Surveying other programming languages such as Python
  • Creating an application using HTML, CSS, and JavaScript
  • Analyzing data using machine learning algorithms and techniques
  • Exploring coding careers paths and different ways to learn how to code

As you enroll for this course/training, keep the following in mind:

  • The course/training materials can be read from beginning to end, but feel free to skip around if you like. If a topic interests you, start there. You can always return to the previous lessons/chapters, if necessary.
  • At some point, you will get stuck, and the code you write will not work as intended. Do not fear! There are many resources to help you, including support forums, others, and me!
  • Code in the course/training materials will appear in a monospaced font like this: <h1>Hi there!</h1>.

I assume you don’t have previous programming experience. To follow along, then, you only need to be able to read, type, and follow directions. I try to explain as many concepts as possible using examples and analogies you already know. I assume you have a computer running the latest version of Google Chrome. The examples in the course/training have been tested and optimized for the Chrome browser, which is available for free from Google. Even so, the examples may also work in the latest version of Firefox. Using Internet Explorer for the examples in this training, however, is discouraged. I assume you have access to an Internet connection. Some of the examples in the training can be done without an Internet connection, but most require one so that you can access and complete the exercises. For data analysis and machine learning, I assume you are able to download and install the Python programming language and associated programming libraries, both of which are available for free. I also assume you have some math background and understand how algorithms work.



What Is Coding?

  • Defining What Code Is.
  • Following instructions
  • Writing code with some Angry Birds.
  • Understanding What Coding Can Do for You.
  • Eating the world with software
  • Coding on the job
  • Scratching your own itch (and becoming rich and famous).
  • Surveying the Types of Programming Languages.
  • Comparing low-level and high-level programming languages.
  • Contrasting compiled code and interpreted code.
  • Programming for the web
  • Taking a Tour of a Web App Built with Code.
  • Defining the app’s purpose and scope
  • Standing on the shoulders of giants

Programming for the Web

  • Displaying Web Pages on Your Desktop and Mobile Device.
  • Hacking your favorite news website.
  • Understanding how the World Wide Web works.
  • Watching out for your front end and back end.
  • Defining web and mobile applications
  • Coding Web Applications
  • Starting with HTML, CSS, and JavaScript 
  • Adding logic with Python, Ruby, or PHP
  • Coding Mobile Applications
  • Building mobile web apps
  • Building native mobile apps

Becoming a Programmer

  • Writing Code Using a Process
  • Researching what you want to build.
  • Designing your app
  • Coding your app
  • Debugging your code
  • Picking Tools for the Job
  • Working offline
  • Working online with Code Academy


Exploring Coding Career Paths

  • Augmenting Your Existing Job
  • Creative design
  • Content and editorial
  • Human resources
  • Product management
  • Sales and marketing
  • Legal
  • Finding a New Coding Job
  • Front-end web development
  • Back-end web development
  • Mobile application development
  • Data analysis

Exploring Undergraduate and Graduate Degrees

  • Getting a College Degree
  • College computer science curriculum
  • Doing extracurricular activities
  • Two-year versus four-year school
  • Enrolling in an Advanced Degree Program
  • Graduate school computer science curriculum.
  • Performing research
  • Interning to Build Credibility
  • Types of internship programs
  • Securing an internship

Training on the Job

  • Taking a Work Project to the Next Level
  • Learning on the Job and after Work
  • Training on the job
  • Learning after work
  • Freelancing to Build Confidence and Skills 
  • Transitioning to a New Role
  • Assessing your current role
  • Networking with developers
  • Identifying roles that match your interest and skills.

Coding Career Myths

  • Educational Myths
  • You must be good at math
  • You must have studied engineering
  • You can learn coding in a few weeks
  • You need a great idea to start coding
  • Ruby is better than Python
  • Career Myths
  • Only college graduates receive coding offers.
  • You must have experience
  • Tech companies don’t hire women or minorities.
  • The highest paying coding jobs are in
  • Your previous experience isn’t relevant


Exploring Basic HTML 

  • What Does HTML Do?
  • Understanding HTML Structure
  • Identifying elements
  • Featuring your best attribute
  • Standing head, title, and body above the rest.
  • Getting Familiar with Common HTML Tasks and Tags.
  • Writing headlines.
  • Organizing text in paragraphs
  • Linking to your (heart’s) content
  • Adding images
  • Styling Me Pretty
  • Highlighting with bold, italics, underline, and strikethrough.
  • Raising and lowering text with superscript and subscript.
  • Building Your First Website Using HTML

Getting More Out of HTML

  • Organizing Content on the Page
  • Listing Data
  • Creating ordered and unordered lists
  • Nesting lists
  • Putting Data in Tables
  • Basic table structuring
  • Stretching table columns and rows
  • Aligning tables and cells
  • Filling Out Forms
  • Understanding how forms work
  • Creating basic forms
  • Practicing More with HTML

Getting Stylish with CSS

  • What Does CSS Do?
  • CSS Structure
  • Choosing the element to style
  • My property has value
  • Hacking the CSS on your favorite website
  • Common CSS Tasks and Selectors
  • Font gymnastics: Size, color, style, family, and decoration
  • Customizing links
  • Adding background images and styling foreground images.
  • Styling Me Pretty
  • Adding CSS to your HTML
  • Building your first web page

Next Steps with CSS

  • Styling (More) Elements on Your Page
  • Styling lists
  • Designing tables
  • Selecting Elements to Style
  • Styling specific elements
  • Naming HTML elements
  • Aligning and Laying Out Your Elements
  • Organizing data on the page
  • Shaping the div
  • Understanding the box model
  • Positioning the boxes
  • Writing More Advanced CSS

Building Floating Page Layouts

  • Creating a Basic Two-Column Design
  • Designing the page
  • Building the HTML
  • Using temporary background colors
  • Setting up the floating columns
  • Tuning up the borders
  • Advantages of a fluid layout
  • Using semantic tags
  • Building a Three-Column Design
  • Styling the three-column page
  • Problems with the floating layout
  • Specifying a min-height
  • Using height and overflow
  • Building a Fixed-Width Layout
  • Setting up the HTML
  • Fixing the width with CSS
  • Building a Centered Fixed-Width layout
  • Making a surrogate body with an all div
  • How the jello layout works
  • Limitations of the jello layout

Using Alternative Positioning

  • Working with Absolute Positioning
  • Setting up the HTML
  • Adding position guidelines
  • Making absolute positioning work
  • Managing z-index
  • Handling depth
  • Working with z-index
  • Building a Page Layout with Absolute Positioning.
  • Overview of absolute layout
  • Writing the HTML
  • Adding the CSS
  • Creating a More Flexible Layout
  • Designing with percentages
  • Building the layout
  • Exploring Other Types of Positioning
  • Creating a fixed menu system
  • Setting up the HTML
  • Setting the CSS values
  • Flexible Box Layout Model
  • Creating a flexible box layout
  • Viewing a flexible box layout
  • And now for a little reality


  • Working Faster with Twitter Bootstrap
  • Figuring Out What Bootstrap Does
  • Installing Bootstrap
  • Understanding the Layout Options
  • Lining up on the grid system
  • Dragging and dropping to a website
  • Using predefined templates
  • Adapting layout for mobile, tablet, and desktop.
  • Coding Basic Web Page Elements
  • Designing buttons
  • Navigating with toolbars
  • Adding icons
  • Build the Airbnb Home Page

Adding in JavaScript

  • What Does JavaScript Do?
  • Using semicolons, quotes, parentheses, and braces.
  • Coding Common JavaScript Tasks
  • Storing data with variables
  • Making decisions with if-else statements
  • Working with string and number methods
  • Alerting users and prompting them for input
  • Naming code with functions
  • Adding JavaScript to the web page
  • Writing Your First JavaScript Program
  • Working with APIs
  • What do APIs do?
  • Scraping data without an API
  • Researching and choosing an API
  • Using JavaScript Libraries
  • jQuery
  • D3.js

Understanding Callbacks and Closures

  • What Are Callbacks?
  • Passing functions as arguments
  • Writing functions with callbacks
  • Using named callback functions
  • Understanding Closures
  • Using Closures

Embracing AJAX and JSON

  • Working behind the Scenes with AJAX
  • AJAX examples
  • Viewing AJAX in action
  • Using the XMLHttpRequest object
  • Working with the same-origin policy
  • Using CORS, the silver bullet for AJAX requests.
  • Putting Objects in Motion with JSON


  • Writing More and Doing Less
  • Getting Started with jQuery
  • The jQuery Object
  • Is Your Document Ready?
  • Using jQuery Selectors
  • Changing Things with jQuery
  • Getting and setting attributes
  • Changing CSS
  • Manipulating elements in the DOM
  • Events
  • Using on() to attach events
  • Detaching with off()
  • Binding to events that don’t exist yet
  • Other event methods
  • Effects
  • Basic effects
  • Fading effects
  • Sliding effects
  • Setting arguments for animation methods
  • Custom effects with animate()
  • Playing with jQuery animations
  • AJAX
  • Using the ajax() method
  • Shorthand AJAX methods


Building Your Own App

  • Building a Location-Based Offer App
  • Understanding the situation
  • Plotting your next steps
  • Following an App Development Process
  • Planning Your First Web Application
  • Exploring the Overall Process
  • Meeting the People Who Bring a Web App to Life.
  • Creating with designers
  • Coding with front- and back-end developers.
  • Managing with product managers
  • Testing with quality assurance

Researching Your First Web Application.

  • Dividing the App into Steps
  • Finding your app’s functionality
  • Finding your app’s functionality: My version.
  • Finding your app’s form
  • Finding your app’s form: The McDuck’s Offer App design.
  • Identifying Research Sources
  • Researching the Steps in the McDuck’s Offer App.
  • Choosing a Solution for Each Step

Coding and Debugging Your First

  • Web Application
  • Getting Ready to Code
  • Coding Your First Web Application
  • Development environment
  • Prewritten code
  • Coding steps for you to follow
  • Debugging Your App


Wrapping Your Head around Python

  • What Does Python Do?
  • Defining Python Structure
  • Understanding the Zen of Python
  • Styling and spacing
  • Coding Common Python Tasks and Commands.
  • Defining data types and variables
  • Computing simple and advanced maths
  • Using strings and special characters
  • Deciding with conditionals: if, elif, else
  • Input and output
  • Shaping Your Strings
  • Dot notation with upper(), lower(), capitalize(), and strip().
  • String formatting with %
  • Building a Simple Tip Calculator Using Python.

Installing a Python Distribution

  • Choosing a Python Distribution with Machine Learning in Mind.
  • Getting Continuum Analytics Anaconda
  • Getting Enthought Canopy Express
  • Getting Python(x,y)
  • Getting WinPython
  • Installing Python on Linux
  • Installing Python on Mac OS X
  • Installing Python on Windows
  • Downloading the Data Sets and Example Code.
  • Using Jupyter Notebook
  • Defining the code repository
Understanding the data sets used in this training.

  • Working with Real Data
  • Uploading, Streaming, and Sampling Data
  • Uploading small amounts of data into memory.
  • Streaming large amounts of data into memory.
  • Sampling data
  • Accessing Data in Structured Flat-File Form.
  • Reading from a text file
  • Reading CSV delimited format
  • Reading Excel and other Microsoft Office files.
  • Sending Data in Unstructured File Form
  • Managing Data from Relational Databases.
  • Interacting with Data from NoSQL Databases.
  • Accessing Data from the Web


Conditioning Your Data

  • Juggling between NumPy and pandas
  • Knowing when to use NumPy
  • Knowing when to use pandas
  • Validating Your Data
  • Figuring out what’s in your data
  • Removing duplicates
  • Creating a data map and data plan
  • Manipulating Categorical Variables
  • Creating categorical variables
  • Renaming levels
  • Combining levels
  • Dealing with Dates in Your Data
  • Formatting date and time values
  • Using the right time transformation
  • Dealing with Missing Data
  • Finding the missing data
  • Encoding missingness
  • Imputing missing data
  • Slicing and Dicing: Filtering and Selecting Data.
  • Slicing rows
  • Slicing columns
  • Dicing
  • Concatenating and Transforming
  • Adding new cases and variables
  • Removing data
  • Sorting and shuffling
  • Aggregating Data at Any Level

Shaping Data

  • Working with HTML Pages
  • Parsing XML and HTML
  • Using XPath for data extraction
  • Working with Raw Text
  • Dealing with Unicode
  • Stemming and removing stop words
  • Introducing regular expressions
  • Using the Bag of Words Model and Beyond.
  • Understanding the bag of words model
  • Working with n-grams
  • Implementing TF-IDF transformations
  • Working with Graph Data
  • Understanding the adjacency matrix
  • Using NetworkX basics

Getting a Crash Course in MatPlotLib

  • Starting with a Graph
  • Defining the plot
  • Drawing multiple lines and plots
  • Saving your work
  • Setting the Axis, Ticks, Grids
  • Getting the axes
  • Formatting the axes
  • Adding grids
  • Defining the Line Appearance
  • Working with line styles
  • Using colors
  • Adding markers
  • Using Labels, Annotations, and Legends
  • Adding labels
  • Annotating the chart
  • Creating a legend

Visualizing the Data

  • Choosing the Right Graph
  • Showing parts of a whole with pie charts
  • Creating comparisons with bar charts
  • Showing distributions using histograms
  • Depicting groups using boxplots
  • Seeing data patterns using scatterplots
  • Creating Advanced Scatterplots
  • Depicting groups
  • Showing correlations
  • Plotting Time Series
  • Representing time on axes
  • Plotting trends over time
  • Plotting Geographical Data
  • Visualizing Graphs
  • Developing undirected graphs
  • Developing directed graphs

Exploring Data Analysis

  • The EDA Approach
  • Defining Descriptive Statistics for Numeric Data.
  • Measuring central tendency
  • Measuring variance and range
  • Working with percentiles
  • Defining measures of normality
  • Counting for Categorical Data
  • Understanding frequencies
  • Creating contingency tables
  • Creating Applied Visualization for EDA
  • Inspecting boxplots
  • Performing t-tests after boxplots
  • Observing parallel coordinates
  • Graphing distributions
  • Plotting scatterplots
  • Understanding Correlation
  • Using covariance and correlation
  • Using nonparametric correlation
  • Considering chi-square for tables
  • Modifying Data Distributions
  • Using the normal distribution
  • Creating a z-score standardization
  • Transforming other notable distributions.

Exploring Four Simple and Effective Algorithms.

  • Guessing the Number: Linear Regression
  • Defining the family of linear models
  • Using more variables
  • Understanding limitations and problems
  • Moving to Logistic Regression
  • Applying logistic regression
  • Considering when classes are more
  • Making Things as Simple as Naïve Bayes
  • Finding out that Naïve Bayes isn’t so naïve
  • Predicting text classifications
  • Learning Lazily with Nearest Neighbors
  • Predicting after observing neighbors
  • Choosing your k parameter wisely


Introducing How Machines Learn

  • Getting the Real Story about AI
  • Moving beyond the hype
  • Dreaming of electric sheep
  • Overcoming AI fantasies
  • Considering the relationship between AI and machine learning.
  • Considering AI and machine learning specifications.
  • Defining the divide between art and engineering.
  • Learning in the Age of Big Data
  • Defining big data
  • Considering the sources of big data
  • Specifying the role of statistics in machine learning.
  • Understanding the role of algorithms
  • Defining what training means

Demystifying the Math behind Machine Learning

  • Working with Data
  • Creating a matrix
  • Understanding basic operations
  • Performing matrix multiplication
  • Glancing at advanced matrix operations
  • Using vectorization effectively
  • Exploring the World of Probabilities
  • Operating on probabilities
  • Conditioning chance by Bayes’ theorem.
  • Describing the Use of Statistics

Descending the Right Curve

  • Interpreting Learning as Optimization
  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning
  • The learning process
  • Exploring Cost Functions
  • Descending the Error Curve
  • Updating by Mini-Batch and Online

Validating Machine Learning

  • Checking Out-of-Sample Errors
  • Looking for generalization
  • Getting to Know the Limits of Bias
  • Keeping Model Complexity in Mind
  • Keeping Solutions Balanced
  • Depicting learning curves
  • Training, Validating, and Testing
  • Resorting to Cross-Validation
  • Looking for Alternatives in Validation
  • Optimizing Cross-Validation Choices
  • Exploring the space of hyper-parameters
  • Avoiding Sample Bias and Leakage Traps
  • Watching out for snooping


Starting with Simple Learners

  • Discovering the Incredible Perceptron
  • Falling short of a miracle
  • Touching the nonseparability limit
  • Growing Greedy Classification Trees
  • Predicting outcomes by splitting data
  • Pruning overgrown trees
  • Taking a Probabilistic Turn
  • Understanding Naïve Bayes
  • Estimating response with Naïve Bayes.

Leveraging Similarity

  • Measuring Similarity between Vectors
  • Understanding similarity
  • Computing distances for learning
  • Using Distances to Locate Clusters
  • Checking assumptions and expectations.
  • Inspecting the gears of the algorithm
  • Tuning the K-Means Algorithm
  • Experimenting K-means reliability
  • Experimenting with how centroids converge.
  • Searching for Classification by k-Nearest Neighbors.
  • Leveraging the Correct K Parameter
  • Understanding the k parameter
  • Experimenting with a flexible algorithm 

Hitting Complexity with Neural Networks

  • Learning and Imitating from Nature.
  • Going forth with feed-forward
  • Going even deeper down the rabbit hole
  • Getting back with backpropagation
  • Struggling with Overfitting
  • Understanding the problem
  • Opening the black box
  • Introducing Deep Learning

Resorting to Ensembles of Learners

  • Leveraging Decision Trees
  • Growing a forest of trees
  • Understanding the importance measures
  • Working with Almost Random Guesses
  • Bagging predictors with Adaboost
  • Boosting Smart Predictors
  • Meeting again with gradient descent
  • Averaging Different Predictors

Real-World Applications

  • Classifying Images
  • Working with a set of images
  • Extracting visual features
  • Recognizing faces using eigenfaces
  • Classifying images
  • Scoring Opinions and Sentiments
  • Introducing natural language processing
  • Understanding how machines read.
  • Processing and enhancing text
  • Scraping textual data sets from the web.
  • Handling problems with raw text.
  • Using Scoring and Classification
  • Performing classification tasks
  • Analyzing reviews from e-commerce
  • Recommending Products and Movies
  • Realizing the revolution
  • Downloading rating data
  • Trudging through the MovieLens data set
  • Navigating through anonymous web data.
  • Encountering the limits of rating data.
  • Leveraging SVD.

And many others, You will learn many things in this powerful course/training which I can't mention here, this training program is a fully packed 9 in 1 course/training program. the course/training has been presented in a step by step simplified guide to study at your own convenient time. you can choose to study all of them at once or switch to the training program that interest you and start studying from there. this online coding course (complete coding training), online coding class, learn coding online and online programming course contain everything you need to know about coding. 

NOTE -: Our Complete Coding Training materials is well details, come with pictures and illustrations that even a dummies can understand it. The training materials is an electronic version which you can read on your Android phone, iphone, iPad and computer system. Our Complete Coding Training materials with our practical training videos is enough to learn coding and make you a professional in Coding field. we are still going to train you one on one live online through WhatsApp and others, we will train you till you become a professional in Coding, certificate will also be issued after completion of the training program. this powerful 9 in 1 training program cost more than 400,000 naira but we are going to give this powerful training out for just 200usd. You can Register Here or Whatsapp, call or message us on 2349077269910 - 2347068895656. you can also email us at indigenousi.tsolution1@gmail.com to register. This is the best online coding course, online coding class, learn coding online and online programming course. Register today and learn the complete A to Z guide of Coding.

NOTE -: Only interested serious minded people who are ready to learn and register should WhatsApp, message or call us. Any information or enquiry you need or want to know about our training program is already on our website, just browse through the footer of the website, you will find the information you need


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