Data science involves extracting insights from data using various techniques and algorithms. It has become one of the most sought-after career options due to its high demand in industries such as healthcare, finance, retail, and technology.
However, becoming a data scientist is not a cakewalk. This article targets the challenges faced by a data scientist and the skills required to overcome them and as a Bonus, we will share with you the best data science certification courses that you must take on to land a job with the top recruiters.
Importance of Data Scientist
In today’s data-driven world, the role of a data scientist has become increasingly important. With the exponential growth of data, it has become essential for organizations to hire professionals who can gather, analyze, and interpret data to gain insights that can drive business decisions.
The role of a data scientist is more than just extracting insights from data using various techniques and tools. Core Data Science Skills involve being responsible for collecting, cleaning, and analyzing large datasets, building predictive models using machine learning algorithms, and communicating their findings to the stakeholders.
Challenges Faced by a Data Scientist
- Data Availability and Quality
- Data Complexity and Size
- Lack of Standardization
- Data Privacy and Security
- Interpretation and Communication of Results
- Keeping Up with Advancements in Technology
- Business Understanding
Skills Required by a Data Scientist
To be a successful data scientist, one must possess a combination of technical, analytical, and soft skills. Here are some of the most critical skillsets required to build a lasting Data Science Career:
Knowledge of Programming Languages (Python, R, Java):
Have a good grip on programming languages to analyze data efficiently. Also, you must be able to work with libraries such as NumPy, Pandas, and Matplotlib to manipulate, analyze, and visualize data.
Data Wrangling and Cleaning:
As a credible Data Science Professional, you must possess the ability to clean and pre-process data effectively. Staying familiar with data analysis techniques such as descriptive statistics, inferential statistics, and hypothesis testing is always a heads-up.
Machine Learning Algorithms:
As a Data Scientist, you should be familiar with popular machine learning algorithms such as linear regression, logistic regression, decision trees, and neural networks. Statistical modeling involves using statistical techniques to build models that explain the relationship between variables in data.
Data scientists must possess a strong foundation in mathematics, statistics, programming, big data technologies, and data visualization tools. To create compelling visualization, you need to be familiar with tools such as Tableau or Power BI that tell a story about the data. They should be able to communicate complex ideas and findings to both technical and non-technical audiences.
Data scientists must possess analytical skills such as:
- Statistical Analysis
- Critical Thinking
Data scientists must possess soft skills such as:
- Business Acumen
3 Best Data Science Certification Courses
1. Data Scientist Nanodegree (Udacity):
This course is all about data science and it teaches you everything you need to know, from collecting and changing data to analyzing it and sharing your findings with others.
This is designed and taught by real-time Data scientists and experts in their fields.
In this course, they will teach you step-by-step ways how to use important tools like Python, SQL, R, Tableau, Spark, and TensorFlow. The course costs $399 a month and takes about 4 months to finish.
2. Data Science Specialization (Coursera x Johns Hopkins University):
This is a series of 10 courses that are Taught by John Hopkins University. You will learn things like how to use R for programming, how to manage data, how to study data to find patterns, and how to use statistics and machine learning.
Throughout the course, you will have quizzes, and assignments, and can get feedback from other students. Upon successful completion of all the courses, you can receive the completion certification from John Hopkins University.
These courses are self-paced and can be learned at any time. Enrolment for this course is free, after completion, you can pay $49 to get the certificate. If you want to have access to more content on the course you have to purchase the materials for which financial aid will be provided.
3. Understanding Data Science (DataCamp):
This is a beginner-friendly course that introduces the fundamentals of data science, such as what data science is, what data scientists do, what tools and methods they use, and what skills they need.
The course uses interactive exercises and videos to explain key concepts and examples. The course also offers a certificate upon completion.
The course is free to access and takes about 4 hours to complete.
Data science is a challenging field that requires a combination of technical, analytical, and soft skills. As an aspiring Data professional, you must be able to overcome the challenges faced in this field, including data availability and quality, data complexity and size, lack of standardization, data privacy and security, interpretation, and communication of results, keeping up with advancements in technology, and business understanding. This is a clear indication that it’s time to get your hands on the world’s most trusted data science credentials from USDSI®, MIT University, and Stanford University, among others listed above. To be a Certified Data Scientist, you must possess the requisite skills and continue to adapt to the rapidly evolving field of data science. I hope this article covered all your doubts about your career as a Data Scientist, the challenges that you might face, the skills that you need to possess, and the best courses to become a certified Data science professional.