6Jun - by aiuniverse - 0 - In Data Science


Has it ever occurred to you that you came across an array of ads of social networking sites of the running shoes you had searched on a different website the previous day? Or the online food ordering app making suggestions about new kebabs joint nearby your area? How about when you are texting someone, and the keyboard suggests you the exact words that you might want to use in your sentence? Or Twitter suggesting tweets that you might be interested in?

These are the real-life applications of data science. Over the past decade, data science has successfully transformed our lives. From Zomato to Tinder, Twitter to LinkedIn, data science is everywhere. It seems that there is an opportunity for data science in every industry imaginable. And data scientist is considered as one of the sexiest jobs today. And without a doubt, the demand is increasing every day.

This is because, today, data scientists can help businesses in numerous ways like mitigating risks and frauds using statistical, network, path, and big data methodologies. They can guide business brands about where and when to deliver their products and personalized customer experiences to meet the customers’ demands. They can identify opportunities, target audiences, and refine them. Further, they empower management to make better decisions, recruit the right talent for the organization, and adopt practices that will help brands achieve their goals and promises. All these are possible by making sense of hordes of data and locating relevant patterns and designs in them, to arrive at actionable insights. Data science helps in industries like pharmaceuticals for drug discovery, healthcare to find the right treatment solutions that help take patient care to the next level.

Therefore, it is becoming evident by the day that there is enormous value in data processing and analysis. So to reap the maximum benefits of this opportunity one needs to have adequate skills in data science. And for adding this extra skillset one may not need formal qualifications in the subject, just the knowledge of the fundamental theory and practical skills are enough to enhance one’s employability and career prospects. Although a certification course can cost much, especially for a student, there are tonnes of affordable data science courses online that can help to kickstart a career in data science.

Data Science Crash Course, John Hopkins University (Coursera)

Designed to give a simple overview of what data science is, how it works, and what it can be used to do. This course offers an introduction to the technical side of data science but is mainly aimed at understanding the big picture for those who need to manage data scientists or data science work. It’s a relatively short course as it consists of one module that can be finished in a week. It can serve as an excellent introduction for those who want to learn the terminology and understand how to build a data science strategy, without necessarily needing detailed instructions on using the technical tools involved.

The Data Science Course 2020: Complete Data Science Bootcamp (Udemy)

It can boost up your resume with in-demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and sci-kit-learn, Deep learning with TensorFlow. Post the course completion, and one can create Machine Learning algorithms in Python, using NumPy, statsmodels, and sci-kit-learn. Also, learn to use Deep Learning frameworks such as Google’s TensorFlowDevelop that a business intuition may use while coding and solving tasks with big data.

The Complete 2020 Big Data and Machine Learning Bundle

This 10-course bundle comprises 68 hours of training in big data and machine learning solutions from some of the top instructors on the Internet. At first, students will learn how to search and analyze data using Elasticsearch, how to harness and organize massive sets of unstructured data using tools like Hadoop, MapReduce, and Apache Spark. After mastering those, one shall learn how to apply machine learning tech to understand the data and draw quicker, better insights from it. Students will get to work with tools like Keras, Python, and Tensorflow and understand how to power machine learning and artificial intelligence.

Introduction to Data Science (Revised) – Alison

A completely free course that breaks down the core topics of the data science process and an introduction to machine learning into three modules, each designed to take around three hours to complete, and concluding with an assessment. Once you’ve worked through that, you can choose from several other similarly bite-sized tutorials covering data programming languages, visualization tools, and techniques such as building clustering and regression models

A data scientist can help us to meet the challenges of the rising demand for data-oriented services and a sustainable future while ensuring the best solutions for the present and future. Hence, they will soon become an integral part of the businesses and various organizations and help the world address significant global challenges, which in turn has far-reaching impacts across the globe. So it is high time to learn that extra skill on the resume.

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