Data science
Becoming a Freelance Data Scientist: A Step-by-Step Guide
Learn how to become a freelance data scientist with this step-by-step guide. Discover the skills you need and start your journey today!
Data science is a large field and includes many different types of data processing. The most common types of data processing are: Data mining, Data modeling, Machine learning, Data visualization.
Data science is not just a buzzword. It’s a new way of solving problems, from predicting the best time to buy an airplane ticket to determining the risk of a heart attack.
Some topics you can read about here: Scatter plots, correlation, t-test, linear regression, logistic regression
Learn how to become a freelance data scientist with this step-by-step guide. Discover the skills you need and start your journey today!
Learn the fastest way to become a data scientist and secure a high-paying job without a traditional degree. Explore the most effective strategies for fast-tracking your learning, including taking advantage of free online resources, enrolling in a bootcamp or certificate program, gaining hands-on experience, and seeking out mentorship. The Data Scientist offers self-paced courses and mentorship programs to help you succeed in the field of data science, even without a traditional degree. Don’t wait – start learning and take the first step towards your dream career today!
Data science and AI for startups Startups and entrepreneurs need to leverage data strategy in order to succeed. Data can provide insights into customer behaviour, market trends, and future opportunities. By understanding how data can be used to inform decisions, startups and entrepreneurs can gain a competitive advantage. I had Read more…
Natural Language Processing (NLP) is the branch of data science primarily concerned with dealing with textual data. It is the intersection of linguistics, artificial intelligence, and computer science. NLP deals with human-computer interaction and helps computers understand natural language better. The main goal of Natural Language Processing is to help Read more…
Sports analytics is a field I feel particularly close to. My PhD was in sports analytics and it had been funded by Tottenham Hotspur FC. I have also released courses on sports analytics. It is one of the areas of application of machine learning that can be so disruptive. Sports analytics is an emerging Read more…
Data cleansing is eliminating or correcting erroneous, incomplete, redundant, or poorly formatted data from a dataset. Routine business operations and large system migrations can impact data reliability. Data cleansing and exploratory analysis take up 80% of data scientists’ time, which is a very common theme discussed in some of the Read more…
In the era of fast-rising interest in big data, data analysis and artificial intelligence, football stakeholders are also looking to machine learning to enhance the success of football throw-ins. Implementing the best analytical strategy on football data not only improves players’ performance but can also save costs for club investors. Read more…
Are you interested in data science? Make sure to join my on-demand webinar where I talk about what it’s like to be a data scientist! The post-covid landscape COVID-19 brought many changes in the world. From AI to cryptocurrencies, to education and the economy, the virus has left us in Read more…
Do you intend to make a career in data science or data analysis but are worried about the right one for you? Are you a graduate interested in exploring the data field as part of your college degree but unsure which pathway to achieve your career success? If you’re a Read more…
Customer churn and data science Customer churn is a major concern for any business. It is the process of customers leaving their service provider for a competitor’s service. This can be due to many different reasons, including financial constraints, poor customer experience, or just general dissatisfaction with the company. Predicting Read more…
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