Data Science

Two Reasons Why Python Corporate Training is Essential

2 min read

While people worry about job displacement caused by AI, business leaders hold an optimistic view.

According to a survey conducted by EY, out of 122 business leaders, more than half of respondents believe that AI will have a positive impact on job creations that boost the economy.

Smart decision-making can drive business growth. Therefore, now more than ever, corporations should place emphasis on training employees with digital technologies to find patterns and make predictions from data, zeroing in on consumer decision journeys.

Discover the 2 reasons why Python training is essential for corporations.

1) Python will dominate the future

Although Python was created in the late 1980s, its interests only start surging in recent years.

Nevertheless, when compared with another popular programming language, R, Python is always lauded as the most powerful, versatile, and easy-to-use programming language for data analysts.

Its learning curve is relatively flat because it is syntactically clear and easily interpretable. Python focuses on code readability and productivity, rendering it a powerful tool to gather, manipulate and visualize data in a faster way.

Now is a great time for Python Corporate Training to stay competitive in the market.  

2) A lack of Data Science talent in the market

To maintain a thriving business in the data-driven digital age, acquiring candidates with a honed IT skillset is essential. Unfortunately, there is no effective and high-quality talent pool that employers can tap into.

If there is a shortage of talents, why not train it yourself? General Python courses are prevalent in Hong Kong, yet customized corporate training is lacking.

Corporate training in Python seeks to tailor to the company’s needs and goals. A bespoke syllabus is available as well where corporations can determine the learning focus areas.   The customized courses are geared to meet the requirements of organizations in terms of training needs, contents, schedule, and venue.


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