DEV Community: LAMBERT KWIZERA

We are inundated with programming languages.

LAMBERT KWIZERA — Tue, 14 Mar 2023 09:04:10 +0000

If you take the time to observe the trends of well-structured training opportunities in the fields of data science, machine learning, or artificial intelligence, you will find that there is, at some point, an emphasis on using programming languages. Interestingly, in some universities across the world, you may find that some graduates from these institutions lack skills in coding and programming. In the marketplace, several employers are looking for smart individuals skilled in coding and programming.

A degree from a university does not necessarily convince employers that you are capable of coding or programming. In fact, I have heard that some companies do not even consider resumes or CVs as the foundation or primary reason to hire someone. Recruiters, although these documents can provide a quick overview of your professional growth, are also looking for portfolios that showcase your abilities to tackle certain world problems or challenges, depending on your area of interest.

A careful observation of graduates reveals that some individuals seem to have a long journey to become adapted to what employers are looking for. Even those graduates who aspire to work independently may lack programming skills.

Therefore, our education system, if its purpose is to train the future generation with a lifelong learning spirit, should be revised to keep up with the demands of the job market. The tech world is moving at a faster pace than the traditional education system.

Lambert KWIZERA

Modern JavaScript for everyone: Mastering Modern JavaScript The Right Way

LAMBERT KWIZERA — Fri, 04 Mar 2022 13:04:40 +0000

By: Lambert KWIZERA
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Introduction
JavaScript is the most popular programming language around the world. It is even becoming one of the most demanding skills. In this digital era, it is very important to learn and master JavaScript. Several organizations, IT companies, research institutions are demanding the mastery of JavaScript. JavaScript is useful in web development and scientific computation tasks, data science, data visualization, and mobile application as well.
The proficient skills of JavaScript do not come at one point in a time. No, they demand the consistent discipline and readiness of teachable and learning spirit. Without them, you won’t go far. You will lag behind, while others are exploring and diving in JavaScript world.

Anyone with learning heart and fresh memory can master JavaScript. Though it is important, it does not require the computer science background. Yes, it is necessary, but the learning aspirations, consistency, acceptance of failures and ability to learn from mistakes are critical to learn JavaScript.

How to master JavaScript
Here I outline for you the right way I think they can be helpful to master JavaScript.

Consistency matters: Don’t tell me you will make it if you are not faithful and seriously committed to learn these stuffs of fearful JavaScript codes, and think that in one second you have master. No, sit down and learn. Great learners know the power of consistency. Make sure the discipline of consistency is hardwired in your blood and bones, or in few words in mind. This world has no pity and has no room for those who don’t like to learn consistently. Look around, scientists have beaten the pandemics because they learn day and night in their laboratories about the deadly viruses, that are killing our parents, siblings and friends. Learn JavaScript consistently. This world is competitive. Period.

Learn step by step considering the structure of the course: One interesting thing in life is that the world is well understood in a structured way. Depending on your objective, normalize to study JavaScript step by step in a structured way. JavaScript curriculums are available. They are designed in a pedagogical way. Human brain likes organization. It becomes troubled when things are not structured way. The problem we have we like to pick up everything without understanding the theory behind or its foundations. Seek to understand how JavaScript works in a structured way. Yes, the objectives you set may force to ignore some of the concepts, but there are JavaScript concepts that are to be mastered to help you understand other advanced concepts.

Project-based learning: While learning in a structured way, I argued above, you should consider thinking of projects. The problem in some of the trainings is the lack of real world projects or simulated projects that can challenge the learners to sense the reality. There are JavaScript projects in internet or in Github. You just type “JavaScript project” as key word in Google. To be precise in search in Google, you must have some basic knowledge in literature search to find a specific project. You will find some projects to attempt with your JavaScript skills. When you feel confident, you have learned, the best way to master and feel the sense of the real world of JavaScript, is to allow yourself get challenged by these projects. They will test powerfully your mastering level and sharpen your programming skills.

JavaScript Bootcamps: Hey, there are more than hundreds of JavaScript bootcamps (whether online or physical), free or paid. Explore them, and sit down and learn. Every year, they are advertised, and come with full updated information. The great thing for these coding camps, they have well-polished marketable skills. Some of them have a well-condensed program that you could have learned in a four-year university program or college.

Do research: One of the problem with some of the educational institutions, is that students don’t get taught to do a research in a well designed manner. One of the good learning outcomes is creativity. This creativity is demonstrated by your ability to do research. The JavaScript requires to have the ability to do a research on certain codes. You will face some coding failures and you have to figure out what caused this failure. Before seeking any assistance outside, do a research. That is secret of great learners.

Collaboration matters also: Do seek collaboration projects in JavaScript world. Contribute, get challenged and grow in mastering. Network with others for the familiarity and exposing your skills, and learn more.

Python for everyone: Mastering Python The Right Way

LAMBERT KWIZERA — Fri, 04 Mar 2022 12:37:15 +0000

The majority of people say that Python, as the programming language, is easy to learn. Yet, the learning journey reveals that the mastery mechanics are not easy. But, much efforts can result in good fruits in mastering the Python. This following could motivate anyone desirous to master this tool.

Python is the most searched language programme in the world;
Several IT giants like Google use Python a lot;
Several companies need Python as the most important skill;
Python is useful in various domain of sciences such as Economics, engineering;
Researchers who study data are opting the Python for data visualization well sophisticated;

Python has gained the quick popularity among the scientific community. The scientists use the Python in the scientific computation. This program helps in development of the websites with the dynamic content. Python solve the problems in data science, web applications, and machine learning.

How to master Python

Consistency: Commitment is part of learning, especially in learning coding. You have to code every day such that you become familiar with Python language. It can be daunting at first, but more efforts in performing coding tasks will bear mastery fruits.

Write: There is a tendency of ignoring the notetaking practice due to the dominance of laptops, but evidence shows that taking notes help retain the information in a powerful way.

Learn to do a research: Every time you are learning coding, you will face a lot of failures. Never give up. Understanding coding failures should push you to learn more. There are a ton of information on Google. You just search about the problem you faced during programming. You will find several solutions to the problem you encountered. Therefore, don’t worry about coding failures or the fact that you find coding or installation is not working. Simply go to google or You-Tube, you will find how some guys have tackled the problem and offered the solution.

Breaks matter in learning: Human beings take breaks to internalize things they enjoy. Whenever you learn coding or programming in Python, be mindful of break. When writing a code and see the output, be happy and celebrate, but take a break and try to internalize the journey you went through to arrive to the output. This will help see the wrong and positive side. Then, after this, you can pause, go out and have some coffee or initiate some chats with friends. This will help have a sharp mind and fresh spirit of learning. For my case, I am learning this important element, I always fail to have break. I have to change.

Learn to collaborate: Though mastering requires a great deal of concentration, working with others on a certain project is key for mastery because it helps you learn from others.

Teach: Teaching is a powerful strategy to learn something and master it. You can find some teaching opportunities, whether in your friends or siblings who aspire to learn about coding in python.

Introduction to Data Structures and Algorithms With Modern JavaScript

LAMBERT KWIZERA — Mon, 21 Feb 2022 21:27:46 +0000

Introduction
JavaScript has pre-established data structures that helpful to solve certain needs and real-world problems. Their mastery makes a difference to the developers. Here we cover arrays, queue, stack and linked list.

Arrays
In JavaScript, an array is the most basic in all data structures. This array stores all data to be used later. Each array has a fixed number of cells decided on its creation, and each cell has a corresponding numeric index used to select its data. Indices help access data that are in array.

To add an element to an array you use these functions : push() and unshift ()
The push() function adds an element at the end of the array.

The unshift () _method adds an element at the beginning of the array.

It is possible to add elements or change the elements by accessing the index value.

It is possible to remove an element from an Array. The _pop() _method to remove the last element from an array. The same method [_pop ()] also returns the returned value.

*Queue *
A queue is an ordered list of elements where an element is inserted at the end of the queue and is removed from the front of the queue. It follows the first-in, first-out (FIFO) principle
A queue has two main operations:

Insert a new element at the end of the queue, which is called enqeue.
Remove an element from the front of the queue, which is called dequeue.

To implement a JavaScript Queue we use an array with these two methods:

Add an element at the end of the array using the push() method. This method is equivalent to the enqueue operation.
Remove an element from the front of an array using the _shift() _method. It is equivalent to the dequeue operation.

The implementation looks like this in Visual Code

The function “Queue ()” function helps store the elements using an array, while the “enqueue ()” helps add an element at the end of the queue, but the “push ()” of an array helps insert the new element at the end of the queue.

Stack **
As a type of data structure, the stack helps keep a list of elements. It works based on the principle of Last In, First out (LIFO), to mean that the most recently added element is the first one to remove.
The stack has two operations: push and pop. The push put an element at the top of the stack while the pop removes an element from the top of the stack.

**Linked list.
Linked List is a linear data structure. But its elements are not stored at the location. The elements are linked using the pointers. A linked list is a linear data structure that represents a collection of elements, where each element points to the next one. The first element in the linked list is the head and the last element is the tail.

Introduction to Data Structures and Algorithms With Python

LAMBERT KWIZERA — Mon, 21 Feb 2022 15:15:57 +0000

This article deals with introducing data structures and algorithms with Python. Data structure is simply a place or location where data are stored and organized. It is a way of arranging data on a computer to facilitate the access and updating of those data. There are two types of data structure: Linear data structure and non-linear data structure. Algorithm is a collection of ways, steps or stages to go through to solve a particular problem. Algorithms are instructions designed and well established or set of inputs created to produce a desired output.

Let us have an example of data structures with Python
Generally, for storing and access to data, these structures called list, dictionary, tuple and set are very helpful. For full control over their functionality in python, the most important data structures are Stack, Queue, Tree, Linked List and others. These structures can be found in other programming languages.

It is important to recognize that there are two kinds of data structures designed to implement in Python:
Built-in Data structures and User defined data structures.

Built-in data structures include: List, Tuple, dictionary and set
User defined data structures: Stack, Queue, Tree, linked list, graph and hashMap.

Built-in data structures
These structures help make programming easier because they were constructed in Python. They help find a solution quickly.

1. Lists
There are designed to store data of different kinds in a sequential way. They have indexes, that can positive or negative, to facilitate the access.
Example:
To create a list, we use a square brackets and put any elements accordingly. If not, you get an empty list as the output

If you want to add an element, you use using the append(), extend() and insert() functions.
Example:

The append() function adds all the elements passed to it as a single element.
The extend() function adds the elements one-by-one into the list.
The insert() function adds the element passed to the index value and increase the size of the list too.

If you want to delete elements:

To delete elements, use the del keyword which is built-in into Python but this does not return anything back to us.
If you want the element back, you use the pop() function which takes the index value.
To remove an element by its value, you use the _remove() _function.

If you want to ACCESS the elements: It is similar to strings in python. You use the index values and hence can obtain the values as needed.

There are other functions:

The len() function returns to us the length of the list.
The index() function finds the index value of value passed where it has been encountered the first time.
The count() function finds the count of the value passed to it.
The sorted() and sort() functions do the same thing, that is to sort the values of the list. The sort() has a return type whereas the sort() modifies the original list.

*2. Dictionaries *
The dictionaries store key-value pairs. To create a dictionary, you use the flower braces or use the dict() function. You will have to add the key-value pairs whenever you work with dictionaries.

To change the values of the dictionary, you use the keys. You access the key and then change the value accordingly. To add values, you add another key-value pair as indicated below.

How to Delete key-value pairs

To delete the values, you use the pop() function which returns the value that has been deleted.
To retrieve the key-value pair, you use the popitem() function which returns a tuple of the key and value.
To clear the entire dictionary, you use the clear() function.

*How to access elements *
You use keys only. You can use either the get() function or just pass the key values and you will be retrieving the values.

There are other Functions
These are the: keys(), values(), items() _functions

3.Tuples
Tuples are similar to lists are with the exception that the data once entered into the tuple cannot be changed no matter what.
To create the tuple, you use the _tuple() function

To access the elements is similar to accessing values in lists.

To append the values: To append the values, use the ‘+’ operator which will take another tuple to be appended to it.

There are other functions that are similar to those of the lists.

4.Sets

Sets are a collection of unordered elements that are unique. To create the sets, using the flower braces but instead of adding key-value pairs, you just pass values to it.

With sets, you can operations, such as union, intersection and so on. You do use these following functions:

The union() function combines the data present in both sets.
The intersection() function finds the data present in both sets only.
The difference() function deletes the data present in both and outputs data present only in the set passed.
The symmetric_difference() does the same as the difference() function but outputs the data which is remaining in both sets.

User-Defined Data Structures
This type of data is not supported by python but can be programmed to reflect the same functionality using concepts supported by python are user-defined data structures.
Data structure that can be implemented this way: Linked list, Stack, Queue, Tree, Graph and Hashmap

Linked list
It is a linear data structure, in which the elements are not stored at contiguous memory locations.
An example:

Stack
It is the linear structure that permits data to be inserted and removed from the same end thus follows a last in first out (LIFO) system. Insertion and removal or deleting is known as push() and pop() respectively.

** Queue**
It is a linear structure that allows insertion of elements from one end and deletion from the other. It follows, First In First Out(FIFO) methodology. The end is called the front of the queue. The other end is the rear end of the queue.

Tree
A tree is a non-linear but hierarchical data structure. Trees are useful for storing data that aren’t linearly connected to each other but form a hierarchy.
Example:

Graph
A Graph is a non-linear data structure consisting of nodes and edges. The nodes called as vertices and the edges are lines or arcs that connect any two nodes in the graph. A Graph consists of a finite set of vertices(or nodes) and set of Edges which connect a pair of nodes.

Hashmap
Hash maps are indexed data structures. They use a hash function to compute an index with a key into an array of buckets or slots.

Categories of algorithms in python
From the data structure point of view, following are some important categories of algorithms
Search − Algorithm to search an item in a data structure.
Sort **− Algorithm to sort items in a certain order.
_Insert*_ − Algorithm to insert item in a data structure.
*Update** − Algorithm to update an existing item in a data structure.
Delete − Algorithm to delete an existing item from a data structure.

Conclusion
Data Structures help store and organize data in python and algorithms are instructions designed to produce desirable outputs.

JavaScript 101: Ultimate JavaScript Guide or Introduction to Modern JavaScript.

LAMBERT KWIZERA — Sat, 12 Feb 2022 12:26:26 +0000

Introduction
Globally, estimates indicate that around 65% of JavaScript to develop software (Statista, 2021). 95 % of over 1.8 billion websites in the world use JavaScript (Kahn, 2021). JavaScript is a scripting or programming language that helps developers design the complex features on web pages. Having said this, one may assume that JavaScript was designed for web development, however, it can be used in data science for visualizing, and analytics, and computing in research (Gans, et al., 2021; Dale, 2016).

Generally, JavaScript is believed for being designed for web development, to help support the user interaction. In it is an universal language for Web, Mobiles, Desktops, Servers, and Databases. Some of the reasons of using JavaScript in web development are that, first, JavaScript helps increase the interactivity. Secondly, it has the compatibility, that means, it provides room for any implementation like in mobile apps. Lastly, JavaScript has a good speed, which is amazing. An execution of the code performs the function and give the results in an efficient way in web and mobile applications.

The simple guide to learning JavaScript

Importantly, it is highly recommended the basics of HyperText Markup Language (HTML) and Cascading Style Sheets (CSS). HTML is an important building block of the Web. It defines the meaning and structure of web content. CSS describes how HTML elements are to be displayed on screen, paper, or in other media. In fact, CSS is the language used to style a Web page.

JavaScript is a language that performs on client-side as well as server-side. It works with HTML and CSS to improve the code functionality and interactivity.

A simple JavaScript Program is indicated below:

To learn better JavaScript, you can select source-code editors at your choice:

Visual Studio Code is a developer-friendly cross-platform that help learn effectively
There are other editors such as WebStorm and Atom.

For mastery, allow yourself get challenged by reading JavaScript books, watching youtube on JavaScripts and attend the bootcamps or CodeCamps. More importantly, it is a good idea to attempt JavaScript projects.

Conclusion

JavaScript is globally used by several web developers to develop the websites and mobile apps. It is even used in data visualization, analytics and scientific computing in research. There are various ways to learn JavaScript and this learning demands the consistency to build up coding skills.

REFERENCES

Statista (2022). Most used programming languages among developers worldwide, as of 2021. https://www.statista.com/statistics/793628/worldwide-developer-survey-most-used-languages/

Kahn, S (2021). What Makes Javascript So Popular. https://generalassemb.ly/blog/what-makes-javascript-so-popular/#:~:text=There%20are%20over%201.8%20Billion,to%20Github's%202020%20Octoverse%20Report.

Dale, K (2016). Data visualization with Python and JavaScript: Crafting a Data-visualisation
Toolchain for the Web. O’Reilly Media, Inc. , 1005 Gravenstein Highway North, Sebastopol,
CA 95472.

Gans, M., Hodges, T and Wilson, G. (2021). JavaScript for Data Science. Chapman and Hall/CRC. https://www.routledge.com/JavaScript-for-Data-Science/Gans-Hodges-Wilson/p/book/9780367422486

Python 101: Ultimate Python Guide or Introduction to Modern Python

LAMBERT KWIZERA — Fri, 11 Feb 2022 10:33:01 +0000

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Python Popularity

In this century, data has become the field of exploration through the world is meticulously and precisely understood. Data has become gold. This exploration is made possible through the availability of well-sophisticated programming language called Python. This programming language is becoming more and more popular. The recent report on the state of data science published by Anaconda revealed that 63% of 4299 individuals from more than 140 countries said they use Python in the online survey conducted from April 14, 2021-May 5, 2021. The same report also revealed that 71% of educators teach Python, and 88% of students reported they are learning Python in preparation to enter the data science/Machine learning field (Anaconda, 2021). Python has gained the growing popularity within the scientific community (Raschka et al., 2020)

Use of the python

This popularity increasingly recognized appears due to the fact that python has several applications in various field of sciences or business. Python can be used in the field of Artificial intelligence (Mihajlović et al., 2020). Python is is “a high-level interpreted programming language, which is widely recognized for being easy to learn” and very useful in workloads in data science, machine learning, and scientific computing (Raschka et al., 2020; Nagpal & Gabrani, 2019). Moreover, python is even useful in network administration, web development, computer games programming and other programs that possess the an integrated support for Python scripts (Nagpal & Gabrani, 2019).

The guide to Python learning

According to World Economic Forum website, some of the top 10 skills needed in future by 2015, that related to mastery of python, I think, are: analytical thinking and innovation, critical thinking and analysis, complex problem solving, and technology design and programming (World Economic Forum, 2020). Therefore, any person with good spirit of learning, as encouraged by World Economic Forum that people should be actively learning and develop learning strategies, can learn python in an easy way.
The easy way to get Python installed in a good laptop is to follow instructions outlined in Anaconda website https://www.anaconda.com/products/individual. If you are a Windows user, Linux user or Mac user, you install the Python accordingly.

Installing Anaconda is straightforward: download the binary and follow the instructions.
You consider these following points:

Install the latest version.
If you are asked during the installation process whether you’d like to make Anaconda your default Python installation, say yes.
Otherwise, you can accept all of the defaults.

To update Anaconda:

Open up a terminal
Type conda update anaconda

Starting the Jupyter Notebook

You can start the Jupyter notebook by:

search for Jupyter in your applications menu, or
open up a terminal and type jupyter notebook
Windows users should substitute “Anaconda command prompt” for “terminal”

If you use the second option, the output tells you the notebook is running at http://localhost:8888/

localhost is the name of the local machine
8888 refers to port number 8888 on your computer

Assuming all this has worked OK, you can now click on New at the top right and select Python 3 or similar.

Here’s what shows up on our machine:

After selecting Python 3:

Then you can type your syntax in the cell:

To learn more about python, you can:

Browse some Python projects on GitHub(https://github.com/trending?l=python).
Have a look at some of the Jupyter notebooks people have shared on various scientific topics (https://nbviewer.org/).
More importantly,use Kaggle and Zindi Africa website
Search Online bootcamps: Lux Tech Academy

Conclusion

Python is a general-purpose programming language, more popular and very useful to perform very sophisticated projects related to data analytics, web development, artificial intelligence and machine learning and scientific computing. Its mastery requires a very consistent spirit of learning.

REFERENCES

Nagpal, A., & Gabrani, G. (2019). Python for data analytics, scientific and technical applications. 2019 Amity International Conference on Artificial Intelligence (AICAI). https://doi.org/10.1109/aicai.2019.8701341

Anaconda (2021). 2021 State Of Data Science Report: On the path to impact. Anaconda

Mihajlović, S., Kupusinac, A., Ivetić, D. & Berković, I. (2020). The Use of Python in the field of Artifical Intelligence. International Conference on Information Technology and Development of Education – ITRO 2020 October, 2020. Zrenjanin, Republic of Serbia

World Economic Forum, (2020).These are the top 10 job skills of tomorrow – and how long it takes to learn them. https://www.weforum.org/agenda/2020/10/top-10-work-skills-of-tomorrow-how-long-it-takes-to-learn-them/