Coincidentally, I just finished the final chapter of this book. I wanted to learn the fundamentals after taking an (execrable) Coursera/IBM course on Python and data science. This book was perfect.
I like this style of introducing a technical topic to a broad audience. It builds incrementally and practically. The prose is clear enough for a layman to gain a conceptual appreciation of the methods even if they skip the exercises. And while the exercises weren’t too demanding, there were many of them, always framed in real world context. For the portion of the audience who will study further, I like to think that the book’s approach towards problem solving and challenging the intuition could be helpful throughout an entire career of statistical thinking.
Learning Go by Jon Bodner is a good choice. It seems to assume that Go is the reader's second (or tenth) language.