How to Upgrade your Skills during the Under-Graduation in Computer Science?

How can I Upgrade my Skills from the initial level to the entire level during the Under-Graduation in Computer Science?


As a Computer Science student, During the graduation of Computer Science, I have learned different types of skills & technologies like Programming skills, Communications skills, Problem-solving skills, and Presentation skills.


If you're interested in preparing for career opportunities in computer science, we recommend getting started with your education as soon as possible. Most high schools now provide a selection of classes in computer science, and the majority of accredited colleges offer both undergraduate and graduate degree programs in computer science and programming. Whichever career path you choose, one thing is certain, learning computer science requires a lot of dedication and study.



We live in a society driven by computer technology. From school to work to socializing, understanding how computers work and how to use them is becoming more essential in many areas of life. The field of computer science takes computing to the next level. More and more students are pursuing an education in computer science and turning their knowledge into lucrative careers in business, engineering, and health care, to name just a few.



Analytical skills
One of the key roles of a computer science engineer is to identify a technical problem and find an apt solution for it. Thus, strong analytical skills are crucial to assess any problem from a different perspective and find the best solution. While working as a computer engineer, you will also be required to explore different options and not simply restrict or adhere to a one solution format.
Creativity
While the ability to solve problems is important, being creative to have unique ideas is also vital to be a skilled engineer. You should be careful while analyzing the operating errors to find the exact cause of the problem.
Problem-solving skills
A computer engineer is also required to solve complicated problems in an organized manner. The problems that engineers attempt to solve are based on real-life scenarios. Thus, to execute and implement the project, you need to detail every step to have an organized outline for solving the problem. While coding, every computer engineer knows the compulsion to get everything right. This also means that engineers need to be quick observers to be able to spot any error, small or big in the program.
Critical thinking skills
Critical thinking skills enable you to be versatile while working on a wide array of projects. It also helps you know the right approach to solve a problem. When you think critically, you are able to analyze the methodologies critically, to find the most suitable one.

                                     Non-Technical Skills


Communication skills
A computer engineer is always a part of a larger team where the team members work simultaneously to achieve certain goals. This means that as a successful engineer, you should be able to interact with your team, exchange ideas and stay updated with the team’s progress towards the long-term goal.
Leadership skills
If you are inclined to move ahead in the field of computer engineering, there will be a certain point where you will be required to lead a team. Thus, for career advancement, possessing leadership skills is essential, otherwise, the roles and responsibilities of an engineer become stagnant despite having decades of experience.
Throughout your career as a computer engineer, you will continue to learn about various software and hardware. With technological advancement, the number of job opportunities for computer engineers is on the rise.  From being able to identify the smallest of errors in lengthy codes to mastering various programming languages, a computer engineer needs to be diverse to be able to succeed in his or her career. 

Presentations skills

Developing presentation skills is an important part of developing team-building skills, as effective presentations can influence and inspire a team.

Presentation skills can be defined as a set of abilities that enable an individual to: interact with the audience; transmit the messages with clarity; engage the audience in the presentation, and interpret and understand the mindsets of the listeners. These skills refine the way you put forward your messages and enhance your persuasive powers.

                          Technical Skills



Programming Skills: The programming skills are known as technical skills. the programming skills learn from programming languages. the various languages are C, C++, Java, Python, .Net, etc.

Programming is a combination of many skills, which means it's not possible to learn it in a quick time, rather it will come with time and experience, but that won't happen automatically.

Image result for programming

Not many programmers practice these essential programming skills. If there is a mandatory problem-solving programming test, I would bet, the average programmer would have been much better. Anyway, here is my list of things, which can help you to become a good programmer.

In order to become a better programmer, you need to be really good at the data structure, algorithms, designing using OOPS, multi-threading and various programming concepts.

the various core subjects and programming languages are studying in computer science as follows:-

  • Programming in C
  • Programming in C++
  • Java/J2SEE
  • .Net
  • Python
  • Data Structure
  • Operating System
  • Software Engineering
  • Software testing
  • Web Technologies
  • RDBMS
  • SQL
  • Compiler Design
  • Computer Network
  • Cyber Security
  • Data mining
  • Cloud Computing
  • Soft Computing
  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • AWS(Amazon web service)
  • Iot(Internet of things)
  • Big-Data Hadoop, etc.




Most Popular Programming Languages to Learn in 2020

Top Most Popular Programming Languages to Learn in 2020.

Every year StackOverflow publishes insights on the developer survey. These insights cover lots of different aspects of the developers around the globe. It includes developers' background, popular programming languages, web frameworks, libraries, tools, databases, platforms in the software industry.



From the last 7 years, JavaScript is the most popular & commonly used language but Python is the fastest-growing language. There’s no change in C#Php & C++ position but Go & Kotlin gained popularity.

There are many programming languages present in the market. Every language has its advantages and disadvantages. So choosing the best programming language on which you should focus can be difficult.

This is also one of the main reasons why I am writing this article. The main motive of this article is to tell you guys the list of best programming language on which you should work in 2020.

1. Python




Python is one of the best programming languages every developer should learn this year. The language is easy-to-learn and offers a clean and well-structured code, making it powerful enough to build a decent web application. 

Python can be used for web and desktop applications, GUI-based desktop applications, machine learning, data science, and network servers. The programming language enjoys immense community support and offers several open-source libraries, frameworks, and modules that make application development.
For instance, Python offers Django and Flask, popular libraries for web development and TensorFlow, Keras, and SciPy for data science applications. 
Though Python has been around for a while, it makes sense to learn this language in 2020 as it can help you get a job or a freelance project quickly, thereby accelerating your career growth. 


2. C#



C# is pronounced as "C-Sharp". It is an object-oriented programming language provided by Microsoft that runs on .Net Framework.
By the help of C# programming language, we can develop different types of secured and robust applications:
  • Window applications
  • Web applications
  • Distributed applications
  • Web service applications
  • Database applications etc.
C# is approved as a standard by ECMA and ISO. C# is designed for CLI (Common Language Infrastructure). CLI is a specification that describes executable code and runtime environment.
C# programming language is influenced by C++, Java, Eiffel, Modula-3, Pascal etc. languages.
Usage applications: Widely used in Enterprise Cross-Applications Development, Web Applications.

3. Java



Java is a programming language and a platform. Java is a high level, robust, object-oriented and secure programming language.

Java was developed by Sun Microsystems (which is now the subsidiary of Oracle) in the year 1995. James Gosling is known as the father of Java. Before Java, its name was Oak. Since Oak was already a registered company, so James Gosling and his team changed the Oak name to Java.

Applications of Java

According to Sun, 3 billion devices run Java. There are many devices where java is currently used. Some of them are as follows:
  1. Desktop Applications such as acrobat reader, media player, antivirus, etc.
  2. Web Applications such as irctc.co.in, javatpoint.com, etc.
  3. Enterprise Applications such as banking applications.
  4. Mobile
  5. Embedded System
  6. Smart Card
  7. Robotics
  8. Games, etc.

4. C#



C++ is a general-purpose, case-sensitive, free-form programming language that supports object-oriented, procedural and generic programming.

C++ is a middle-level language, as it encapsulates both high and low-level language features.

Applications of C++

By the help of C++ programming language, we can develop different types of secured and robust applications:
  • Window application
  • Client-Server application
  • Device drivers
  • Embedded firmware etc.
5. Javascript


JavaScript (js) is a light-weight object-oriented programming language that is used by several websites for scripting the webpages. It is an interpreted, full-fledged programming language that enables dynamic interactivity on websites when applied to an HTML document. It was introduced in the year 1995 for adding programs to the webpages in the Netscape Navigator browser. Since then, it has been adopted by all other graphical web browsers. With JavaScript, users can build modern web applications to interact directly without reloading the page every time. The traditional website uses js to provide several forms of interactivity and simplicity.


Although, JavaScript has no connectivity with Java programming language. The name was suggested and provided in the times when Java was gaining popularity in the market. In addition to web browsers, databases such as CouchDB and MongoDB uses JavaScript as their scripting and query language.

Application of JavaScript:
JavaScript is used to create interactive websites. It is mainly used for:
  • Client-side validation,
  • Dynamic drop-down menus,
  • Displaying date and time,
  • Displaying popup windows and dialog boxes (like an alert dialog box, confirm dialog box and prompt dialog box),
  • Displaying clocks etc.

6. PHP


PHP is an open-source, interpreted, and object-oriented scripting language that can be executed at the server-side. PHP is well suited for web development. Therefore, it is used to develop web applications (an application that executes on the server and generates the dynamic page.).

  • Running with PHP is simple
  • Functional and Object-Oriented Programming
  • Large Open Source Software Community
  • A reasonably good system of automation tools available for testing and deploying.
Applications of PHP

Web Applications
Content Management Systems
eCommerce Applications.

7. SQL



SQL was developed at IBM by Donald D. Chamberlin and Raymond F. Boyce. This language was made available publicly in 1979.

Cons:
  • Powerful query language.
  • Optimized for large numbers of table rows.
  • Fast for searching and querying of data.
  • High availability and consistency of data.
  • Fast for retrieving data from multiple tables.
Pros:
  • Difficult to convert data from Objects into database tables
  • It can only run on a single server, so increasing speed means upgrading hardware.
  • As SQL databases run on a single server so in case if the server stop working, then the database shouldn't be accessed.

8. Kotlin



Kotlin is a general-purpose, statically typed, and open-source programming language. It runs on JVM and can be used anywhere Java is used today. It can be used to develop Android apps, server-side apps and much more.

Kotlin was developed by JetBrains team. A project was started in 2010 to develop the language and officially, first released in February 2016. Kotlin was developed under the Apache 2.0 license.


Features of Kotlin

  • Concise: Kotlin reduces writing the extra codes. This makes Kotlin more concise.
  • Null safety: Kotlin is the null safety language. Kotlin aimed to eliminate the NullPointerException (null reference) from the code. Interoperable.
  • Interoperable: Kotlin easily calls the Java code in a natural way as well as Kotlin code can be used by Java.
  • Smart cast: It explicitly typecasts the immutable values and inserts the value in its safe cast automatically.
  • Compilation Time: It has better performance and fast compilation time.
  • Tool-friendly: Kotlin programs are build using the command line as well as any Java IDE.
  • Extension function: Kotlin supports extension functions and extension properties which means it helps to extend the functionality of classes without touching their code.

9. Go programming language



Go language which is also known as golang is developed at Google in 2009 by Robert Griesemer, Ken Thompson, and Rob Pike.
  • Go is a really fast language as it is compiled to machine code
  • Its syntax is small compared to other languages, and it's easy to learn.
  • Offers standard library to provide handy built-in functions for working with primitive types
  • Go makes concurrent programming easy.
Applications: 

Console utilities.
GUI applications.
web applications.


10. Swift


Swift is a general-purpose, multi-paradigm, compiled programming language for developing iOS and OS X tvOS, watchOS applications. It is developed by Apple Inc. It is a powerful and intuitive language that is easy to learn. Swift code is safe, precise and runs very fast.

Swift follows Objective-C runtime library which allows C, Objective-C, C++ and Swift code to run within one program. Swift is built with open source LLVM compiler and included in Xcode since version 6.

Pros:
  • The Swift program codes are near to natural English, so it is easy to read
  • Easy to add new features to this language which makes swift high- level language
  • The language does not have a long code line.
  • Automatic Memory Management feature prevents memory leaks.
Cons:
  • With the continues updating of swift versions of Apple, Swift is somewhat unstable
  • As it is a new programming language the pool of Swift developers is very limited
Usage applications:




Best Data Science Training Certification Program

5 Best Data Science Certifications course

once you have decided to be certified for Data Science Program. It's time to choose one that suits you perfectly. Now, days the various Data Science certifications program offered on both online and offline modes. In this write-up, we would be focusing on the top-rated online certification program.

1. Data Science Program with Simplilearn


Simplilearn - Online Certification Training Course Provider

The Simplilearn Provides the online certification program on Data Scientist Master's program in collaboration with IBM. Experience world-class training by an industry leader on most in-demand  
Data Science and Machine learning skills. Gain hands-on exposure to key technologies including R, SAS, Python, Tableau, Hadoop, and Spark. Become an expert Data Scientist today.

About the Program 

The program developed in collaboration with IBM.

IBM is the second-largest Predictive Analytics and Machine learning solutions provider globally. 
the joint partnership with Simpleilearn and IBM introduces students to integrated blended learning, making them experts in Artificial intelligence and Data Science. The program in collaboration with IBM will make students industry-ready for Artificial intelligence and Data Science job roles.

Upon completion of the master's program, you will receive the certificate from IBM and Simplilearn
in the Data Scientist courses on the learning path.


2. Edureka



Image result for data science logo of edureka

Opportunities for data scientist-one of today's hottest jobs are rapidly growing in response to the exponential amounts of data being captured and analyzed. In the competitive working landscape,
which sees an endless flow of information and communication, data scientists help major decision makers shift from ad-hoc analysis to an ongoing conversation with data. specially Edureka offers you certification courses in Data analytics, predictive modeling, and others to help kick-start your career as a Data Scientist.

At Edureka! you can learn at your own pace, at your own time, from a location of your choice. But the Edureka experience is much more than this and caters to every single aspect of Data Scientist Skill Development.

Edureka has a specially curated Data Science Masters Course which helps you gain expertise in Machine learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, Naive Bayes. You will learn the concept of Statistics, Time Series, Text Mining, Deep Learning, Big Data, etc.

Edureka Data Science Course link

Data Science Masters Program Curriculum

3. Coursera


Image result for coursera data science logo

This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.

In this course, you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data.

Coursera Data Science Course link



4.Udemy


Image result for udemy data science logo

The course provides the entire toolbox you need to become a data scientist. Fill up your resume with in-demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and sci-kit-learn, Deep learning with TensorFlow.

Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!) and Start coding in Python and learn how to use it for statistical analysis.
Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data and Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross-validation, testing, and how hyperparameters could improve performance.

The data scientist is one of the best-suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace.     
However, the supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist.  

Udemy Data Science Course Link

5. Intellipaat

Image result for intellipaat data science course



Intellipaat Data Science course training lets you master data analysis, R statistical computing, connecting R with Hadoop framework, Machine Learning algorithms, time-series analysis, K-Means Clustering, Naïve Bayes, business analytics and more. In this Data science online course and certification, you will gain hands-on experience in Data Science by engaging in several real-life projects in domains of banking, finance, entertainment, e-commerce, etc. So, get the best online Data Science courses training from top data scientists!

About Data Science Online Course

This is a complete Data Science boot camp specialization training course from Intellipaat that provides you with detailed learning in Data Science, Data Analytics, project life cycle, data acquisition, analysis, statistical methods, and Machine Learning. You will gain expertise to deploy Recommenders using R programming, and you will also learn data analysis, data transformation, experimentation, and evaluation.

Intellipaat Data Science Course Link

Data Science Projects

Project 1: Augmenting retail sales with Data Science.

Project 2: Analyzing the pre-paid model of stock-broking.

Project 3: Cold Start Problem in Data Science.

Project 4: Recommendation for Movie, Summary.

Project 5: Prediction of Pokemon dataset.

Project 6: Loan Prediction.

Project 7: Book Recommender System.

Project 8: Census Income.




The Successful Software Devloper Engineer Journey (2019-2022).

I am 23 years (will turn 24 this March) old Software Engineer (SDE1 - Mobile) in Bangalore. I started my career as an intern in May 2019 whe...