From the course: Complete Guide to AI and Data Science for SQL Developers: From Beginner to Advanced

Necessary skills for data science - SQL Tutorial

From the course: Complete Guide to AI and Data Science for SQL Developers: From Beginner to Advanced

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Necessary skills for data science

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- [Instructor] All right. Let's now dive deep into the world of a data scientist. You're about to discover the essential skills to become an expert in this field. Before you jump in, it's important for you to grasp why we're focusing on the role of a data scientist in this course. It's positioned at the cutting edge of AI solutions. Data scientists help bridge the distance between raw data and the actionable insights you can use. Your unique skills as a data scientist will equip you to craft and refine the AI tools and techniques you'll rely on. Let's take a look at the foundational skills that will shape you as a trailblazing data scientist. A data scientist stands on a foundation in math and statistics. You'll use these skills to design experiments, work with data, and optimize models. You'll use things like experimental design, where you craft well-planned experiments to gather meaningful data, linear algebra and calculus, where you use mathematical tools to help analyze data patterns, machine learning, where you understand how machines learn from data to make predictions, supervised learning, which teaches machines to learn from labeled or pre-categorized data, unsupervised learning, which helps machine find hidden patterns in unlabeled or un-categorized data, model optimization, which improves models for better prediction accuracy, and deep learning, which explores cutting edge techniques like neural networks for complex data analysis. As a data scientist, you'll not only have a strong grasp of programming, but you also apply these languages in various ways. Using languages like R, Python, and SQL, you'll cleanse and prepare data, filter out noise, handle missing data points, and get your data in the right shape for analysis. Statistical analysis, apply statistical tests and procedures to understand underlying patterns. Data visualization, create charts, graphs, and interactive visuals to make sense and represent data trends. Predictive modeling, use historical data to forecast future events or trends. Machine learning, train models to classify data, predict outcomes, or even recommend products. Database management. With SQL, manage and retrieve data efficiently from vast databases. Data scientists don't just crunch numbers. They also need to communicate their findings effectively. So you'll need the ability to convey insights to senior leadership where you present complex data in a way that just about anyone can understand. The art of storytelling. This is where you weave data into compelling narratives. Effective visualization skills, where you create stunning visuals that reveal the story behind the numbers. You'll also have the ability to collaborate with other team members where you work in harmony with other data professionals. And finally, you'll transform data into actionable insights and help businesses make critical data-driven decisions. One more thing to become an outstanding data scientist. Domain knowledge is key. This means understanding how things work in a specific industry, including its unique challenges. It involves having a good grasp of business concepts related to that domain, so you can link data insights to practical business strategies. Okay, up next, you'll explore some real world business use cases where data science is making a big difference today.

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