Hello @channel. Is there anyone stuck on yesterday's content? I would like to answer a few questions before we go on. Tomorrow, we will be having a class at 8:00 PM EAT (GMT + 3) which will be led by Wycliffe Bosire Data Scientist at BAT.
In your data science career path, make sure to: 1). Master linear algebra and statistics basics. Data science is a heavily math-based field, so it is important to have a strong foundation in linear algebra and statistics. This will help you to understand the algorithms and techniques that are used in data science.
2). Learn algorithmic framework. Algorithms are the essential building blocks of data science. By understanding the basic algorithmic framework, you will be able to design and implement your own algorithms to solve complex data science problems.
3). Go beyond algorithms, understand their structure. It is not enough to simply understand how to use algorithms. You should also have a deep understanding of how they work and how to choose the right algorithm for a given problem.
4). Be proficient with Python and its libraries. Python is the most popular programming language for data science. It is important to be proficient in Python and its libraries, such as NumPy, Pandas, and scikit-learn.
5). Get friendly with SQL. SQL is a database query language that is used to retrieve and manipulate data from databases. Data scientists often need to use SQL to access and prepare data for analysis.