In our article about the 10 highest-paying AI-related jobs around the globe, data scientists ranked second on the list, with an average annual salary of $170,000.00.

A data scientist is a professional who uses data to help businesses make decisions. They apply mathematical, statistical, and programming skills to collect, analyze, and interpret large amounts of data. They also use data visualization techniques to present their findings and insights in a clear and compelling way.

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The Role and Importance of Data Scientists in the AI Industry

Basically, data science is a field that uses algorithms, procedures, and processes to examine large amounts of data to be able to detect patterns, generate insights, and create decisions using math and statistics, programming, analytics, AI, and even machine learning.

Ultimately, data science plays a significant role in the AI industry as it aids in the processing, analyzing, and interpreting of large amounts of data, as well as selecting the relevant and informative data needed. It can also be used to find and extract data from legitimate sources and help improve the learning process of AI tools integrated into websites and applications. 

Do you believe you possess the necessary skills to become a data scientist in the future?

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Embark on an AI Career Journey: Top Online Courses and Learning Paths for Aspiring Data Scientists

Top Online Platforms Offering Data Science Courses

Among the online platforms available today, Coursera provides online courses through which users can earn a degree or professional certificate in data science.

Additionally, Coursera offers the “IBM Data Science Professional Certificate” course. The course is expected to help its learners kickstart their careers in data science and machine learning by teaching them Python, SQL, data analysis, data visualization, and machine learning using the IBM Cloud and real-world data sets. Though it is not free, financial aid is available for those who cannot afford it.

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Lastly, Udemy offers numerous online courses and modules related to data science across various fields, with prices ranging from ₱700.00 to ₱4000.00.

Project Smarter Philippines through Data Analytics, R&D, Training, and Adoption (SPARTA) also has learning paths to becoming a data analyst and data scientist.

The project is supported by the Development Academy of the Philippines, Department of Science and Technology, DOST-PCIEERD, and Analytics Association of the Philippines.

Comprehensive Learning Paths to Become a Data Scientist

Typically, high-paying jobs require high-quality employees; thus, to be able to be competitive enough and be the “top-tier” data scientist in this industry, it is better to:

Learn programming languages. Proficiency in one or more programming languages commonly used for AI and data science, such as Python, R, Java, and C++, is essential. You also need to be familiar with the libraries and frameworks that support AI and data science tasks, such as TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.

Acquire knowledge in statistics, math, and problem-solving. Statistics is one of the foundations of data science, as it helps firms understand the data, perform hypothesis testing, draw inferences, and make predictions. You need to learn the basic mathematical concepts and methods of statistics, such as descriptive statistics, probability, distributions, sampling, confidence intervals, hypothesis testing, and regression, to be able to apply them to real-world data solving. 

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Learn about data collection and cleaning. After data collection, you must understand how to clean and store the data gathered from various sources. Data cleaning is the process of preparing the data for analysis by removing errors, inconsistencies, outliers, missing values, and even duplications. 

Learn database management. After data cleaning, you should know how to use Python libraries such as Pandas and NumPy to manipulate, transform, and clean the data. You could also use tools that are able to handle large databases. 

Develop expertise in machine learning and deep learning. Machine learning and deep learning are the branches of data science that deal with building and training models that can learn from data and make predictions or decisions. You need to be familiar with the principles and methods of these branches, such as supervised learning, unsupervised learning, reinforcement learning, neural networks, convolutional neural networks, recurrent neural networks, natural language processing, and computer vision.

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Master data visualization. You should be capable of communicating your findings and insights from data analysis using visual tools and techniques. You also need to be able to create interactive dashboards and charts using tools like Tableau, Matplotlib, Seaborn, and Plotly.

Engage with the community. Data Science in AI is a fast-paced industry. Thus, connecting to other data scientists in the community is a win-win situation to stay updated with the latest developments. You can also learn from their experiences, receive tips and advice, and connect with those you can work with. 

Once you have done almost all of these tips, you can be confident and surely call yourself a “top-tier data scientist.”

Future Job Prospects for Data Scientists in AI

The application of data science in the AI industry is indeed powerful and useful. In fact, many data scientists are known today for being builders and innovators of AI tools, including Andrew Ng, the founder of deeplearning.ai; Fei-Fei Li, the founder of the AI4ALL movement; Andrej Karpathy, the senior director for AI at Tesla; and Yann LeCun, the chief AI scientist at Facebook. 

The field is also versatile; data scientists could be freelancers, consultants, analysts, researchers, and even overseers of the product development process.

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Indeed, data scientists are in high demand, and the field is expected to continue its growth in the upcoming years. As businesses and organizations collect more and more data, they will need data scientists to help them make sense of it all.

If you are passionate about data science and are willing to put in the work, then you can have a successful career in this field. Data scientists are making a real impact on the world, and you can be a part of that.

Are you eager to use data to solve real-world problems? Do you have a strong foundation in math, statistics, and programming? If so, then a career in data science may be the perfect fit for you.

This article is published on BitPinas: Embark on an AI Career: Essential Online Courses for Aspiring Data Scientists

Disclaimer: BitPinas articles and its external content are not financial advice. The team serves to deliver independent, unbiased news to provide information for Philippine-crypto and beyond.

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