Xccelerate
Develop your career with the most in demand tech skills offered by Xccelerate in Hong Kong. Enterprise training available.
Corporate Training vs Tech Training. Corporate training or technical training - Which should you invest your training budget in?
Both are popular terms and seem self-explanatory. But, how are these different in practical terms, and which provides better bang for your buck? Corporate training is actually a general term, and programs are traditionally aimed at improving soft skills of employees while “corporate” technical training programs are aimed at improving technical expertise of your employees.
Skills in traditional Corporate Training: Communication, Insightfulness, Empathy, Critical Thinking, etc Skills in Tech Training: Machine Learning, Python, Data Science etc. Read Also: Hiring Skilled Employees VS Training Employees Internally. Hiring Vs Training. The major dilemma for most organizations is which business solution to undertake: whether to hire skilled employees or to up-skill existing employees internally.
Either solution impacts the firm’s short term and long term goals, it’s the workplace culture of its people. Why Are Employers Spending More Money in Tech Training. As competition for talent is growing every day, investing in employee development and training can do wonders in getting a competitive advantage over other companies.
Survey reports note that successful employers are spending more money into tech training than ever before. The many benefits in the short and long run are triggering them to invest a good portion of their funds in employee development programs. Whilst most companies say they want to drive employee growth and development for the future of work, very few companies have yet to start to confront the issues. Companies, like AT&T’s initiative to retrain nearly half of its workforce, vowed to put aside 1 billion USD into the initiative, after discovering less than half of its workforce was adequately skilled to the company to remain competitive.
As employees feel appreciated and more valued, it eventually results in increased employee loyalty. Xccelerate. You have decided to go for a data science career or you might have thought to transition from the academic world to handsomely paying jobs in data science.
But how could you make sure you have embarked on the right career path? How do you know you will end up with the job you have ever hoped for? Who would tell you precisely what skills/projects it takes to be the chosen one among other applicants? How to Become a Successful UX Designer. UX design is a great profession for people who are technically brilliant and amazingly creative.
Being a successful UX designer is not a simple task as it needs a lot of patience, determination, hard work and willingness to improve every day. Being one of the highest paid professions today, this is among the most demanding job profiles as well. This is one of the stress free job profiles of the times if you really enjoy doing it and have a passion for the same. As organizations realize the significance of quality user experience for continual success, they are seriously looking forward to hiring the best UX designers available for their firm. Top 10 Front-end web development trends 2020. Web development experts and the strategic use of technologies are two of the biggest drivers of business success and customer engagement on digital platforms.
To empower their online presence, companies need to hire web developers who are aware of the latest web development environments, tools, frameworks and related practices. Since the technological space is incessantly evolving, it is important to keep up with new emerging trends and adopt business-friendly tactics. Role of Software Engineers in Startups. According to LinkedIn reports, the demand for software engineering jobs has almost doubled in the past 2 years. startups have also made a big impact in these figures as most or all of the top startup organizations need software engineers.
This is simply because all of the companies need quality software irrespective of their tech orientation or size. However, a common question asked is regarding the trigger behind engineers choosing startups over well established companies like Microsoft, Apple, Amazon and Facebook. Most of them pointed out that startups provide faster career growth paths and they get a chance to explore their competency. Moreover, they get an opportunity to work closer with related teams of the firm.
This gives an overall novel dimension to the learning possibilities at work. What is Machine Learning? Types, Examples. What is Machine Learning?
Machine Learning (ML) is an application of Artificial Intelligence (AI) that enables systems to automatically learn and improve from experience without being explicitly programmed. Therefore, instead of writing the code, you need to feed the data to the generic algorithm, and the algorithm/ machine builds the logic based on the given data.
It focuses on the development of computer programs that can access data and use it to learn themselves. Hence, the main aim of machine learning is to let the computers learn automatically without human intervention or assistance and adjust actions accordingly. Generally, ML algorithms are trained using a training data set to create a model. Data Scientist Salary in Hong Kong. 10 Most Important Machine Learning Algorithms for Data Science. From the word go in the world of digital computing, Algorithms have been the smartest answer to complex questions.
At their core, they are powerful programming models trained to process given datasets in order to produce predictive results of highest accuracy. In this article, we are going to take a small trip through the 10 best machine learning algorithms essential for data scientists and their career. It includes types of algorithms, the purpose and methods of model training and their actual industrial applications. Is a Data Science Bootcamp worth it to get a Data Science Job. There is a flood in Data science bootcamps everywhere.
IBM statistics state that there will be as many as 2.7 million data scientist jobs in 2020 in U.S. alone. On the other hand, Glassdoor sees the Data Scientist job as being the best job in high demand in America based on job openings, salary and job satisfaction. In reality, Data science graduates enjoy a massive employment rate with more starting salary than often offered by many other technical jobs. 10 Ways to Activate Your Data Science Career. There is no wonder why Data Science is the hottest topic of the decade. LinkedIn has named data scientist as the most promising career in 2019 and Glassdoor called it the best job in America. The best part is that choosing a career in data science will not only help you earn a good salary but also gives a high level of job satisfaction.
Reports say that it tops the chart in the survey of jobs with most job satisfaction. How to Get a Job After a Coding Bootcamp. Coding bootcamps are a rewarding learning experience with career builder prospects. Such bootcamps are nowadays a challenging way to interact with peers, augment new skills and expand your existing knowledge. However, the biggest concern after completing from coding bootcamp is whether or not you will get a job after coding bootcamp. Being a coding bootcamp student, you might wonder how you could put yourself out there in the real world to get a dream job and carve a solid career. If you are in your early 20’s, when you spend a big great slice of time working to support your living, you seek some good fortune in this domain.
Top 10 Uses of Python in Business. All the latest and greatest happenings in the world of data science and machine learning these days seem to end up with Python programming language. In this blog, our main focus is Python language as we go on explaining the top 10 uses of Python in business today. It is incontestable that Python has become a highly preferred and fastest-growing language as indicated by Stack Overflow’s 2019 Developer Survey. Python has been among the top 10 popular programming languages in 2017, as TIOBE Programming Community Index indicates.
For developers ploughing — or wanting to plough — the field of both data science and AI-based deep learning algorithm development, Python is an omnipotent and robust general-purpose, interpretable, high-level programming language. How to get a Software Developer Job without a CS Degree. A software developer is currently one of the most desirable jobs for many young career builders, even amongst those whom did not pursue CS degrees as an undergrad.
Data Science for Startups: An Introduction. This article explores the use of data science for startups that essentially covers the importance and impact of the data pipeline, data extraction and tracking, predictive modeling, and business intelligence. We are going to absorb the brief idea of building data platforms and functional features to utilize the best power of data, including the entire data discipline. Since in recent years, the data science domain has evolved in its scope, opportunities, and promises, it is important for data scientists to realize the effective role and value of dynamic data analysis, scalable models, deep learning, data processors and running experiments. Top 10 Python Libraries for Data Science 2020.
Why is Python Considered a High-Level Programming Language? Software developers have to dabble in a gamut of available programming languages used for building web services, websites and enterprise applications before settling for the one they feel most comfortable with. However, as the programming space is constantly open to new innovations and improvements, they need to learn the changing aspects of programming.
Ultimately, the one language they choose to master should be able to address the whole spectrum of requirements. Python, of all, has recently emerged as the best pick as a high-level programming language as confirmed by IEEE study. The Python language was founded in 1991 by the software developer Guido Van Rossum with the intent to make things easy for developers. Ever since then, the language has undergone several versions and updates and is now used in many big enterprises and IT companies. Trending Data Science Skills for 2020.
Although the international popularity of data science as a career only caught up across the world recently, its echoes found its way long back in 2010. The latest explosion of data science opportunities, especially among the leading business capitals has made it one of the most booming and sought-after fields. According to an IBM report, there is going to be 110,000 fresh job roles for data science masters by 2020 with 15% growth. There is, no doubt, a huge demand in data science skills on a global technology podium which comprise of statistics, math, Python programming, machine learning, NLP and data visualization. 10 Highest Paying IT Jobs for 2020. IT today is a mixed bag. It may have lost the early shine, but it is still gold. Is Data Science Difficult to Learn? How to Switch to a Career in Data Science.
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