Data science is one of the top career choices today. Why? It pays well and offers steep career growth compared to any other current tech careers. But it is also a challenging career, requiring expertise in multiple subjects including statistics, mathematics, machine learning, programming, and more. So there’s no surprise that it is one of the most lucrative jobs out in the market.
Being a new field and still in nascent stages, data science doesn’t come easy. It’s complex and difficult to grasp. One of the ways to learn data science, especially for complete beginners, is to take data science certification course. The courses offer a comprehensive and simplified way to learn and implement data science, readying candidates to kick start their data science career.
We will delve into the details of popular data science certification courses in the later part of the article.
USA is one of the top destinations that employs data scientists. The country also boasts of some of the best data analytics companies in the world. As organizations and start-ups in the US increasingly realize the value of data-driven decision making, demand for data science professionals is increasing in the country. Several start-ups have emerged that rely completely on data science for delivery of their services. In brief, demand for data science professionals in the US is more than anywhere else across the globe.
What’s more, data science is a challenging domain. It requires a gamut of skills, starting from statistics, mathematics, programming, to machine learning. All this can’t be learned in a week, so let alone becoming a data scientist, you won’t even become a data analyst. Thus, learning data science should start with commitment, sincerity, and determination. It can take anywhere between 6-12 months to effectively learn data science, to deliver on point.
How to learn data science?
Data science is an interdisciplinary field, which requires strong problem-solving skills and unparalleled analytical aptitude coupled with knowledge of computer science. Specifically, it requires:
- Programming – R and Python are the most widespread programming language in the field of data science. Java, SQL, and C++ are often used to work with big data and related tools. Thus, knowledge of programming is imperative to build a successful career in data science.
- Statistics – This is the foundation of data science. Common concepts like standard deviation, dispersion, central tendency, probability max function, etc. are critical for result-oriented tasks. At the near step of building a model, statistical techniques are used.
- Data structures and algorithms – Data science professionals use code to implement various statistical techniques and machine learning algorithms. An important part of algorithms and structures behind the work of data structures and algorithms in data structures. To understand machine learning algorithms, it is important for data science professionals to know data structures and algorithms.
- Machine learning algorithms – Decision trees, KNN (K-nearest neighbor), linear and logistic regression, random forest, SVM (Support Vector Machines), Gradient boosting, Naïve Byes, Linear discriminant, etc. are a few popular and frequently used algorithms to build machine learning models.
- Software – In addition to the above skills, data science professionals are required to be proficient in a few popularly used analytics software like Hadoop, Tableau, Spark, Hive, etc.
These skills can be acquired by taking data science certification course.
Best data science certifications
ne the best ways to acquire and demonstrate data science skills is to take a data science certification. Globally-recognized and vendor-neutral certification proves the holder’s knowledge and competency in implementing data science skills. The following are a few best data science certifications in the USA and in the industry.
1. CCP Data Analyst ( Cloudera Certified Professional Data Analyst)
This is an entry-level data science certification for data science aspirants that proves the holder’s knowledge of Hadoop, Hive, and Spark and using them to accomplish various data science related tasks. This certification, however, equips the holder with the skills to work in Cloudera environment.
- ABDA (Associate Big Data Analyst)
This certification is offered by DASCA (Data Science Council of America). ABDA is a globally-recognized, vendor –neutral, and platform agnostic data science certification that equips you with the data science skills which world’s top employers look for while hiring data science professionals. This entry-level certification is perfect for aspirants looking to embark on a global career in data science.
- SDS ( Senior Data Scientist)
This is a senior-level data science certification for experienced data scientists. This certification is offered by DASCA (Data Science Council of America). The certification is equally valuable for data analysts and mid-level data science professionals who are looking to transition to data scientist roles. SDS is the world’s most valuable third –party data science credential that proves your knowledge and competence, needed to achieve organizational goals.
- EMC Proven Professional – Specialist Data Scientist
This an advanced data science certification for experienced data science professionals who want to further develop their skills and learn advanced analytical techniques using Hadoop, Spark, Hive, Pig, and other widely used analytics applications. Taking this certification will help you move to the next level in your data science career.