My Data Camp Journey
You probably heard that the data scientist labeled as “sexiest job of the 21st century” from Harvard University. If you heard, there is also a high probability that you heard the Datacamp name or even you get their free courses. At least that what I found when I search the data science courses. Data camp was one of the professional platforms that cover all courses that I want to take it 👌. And in this post, I will mention the datacamp courses, advantages, disadvantages, and so on…
“DataCamp offers interactive R, Python, Sheets, SQL and shell courses. All on topics in data science, statistics and machine learning. Learn from a team of expert teachers in the comfort of your browser with video lessons and fun coding challenges and projects.”
I enroll the Data science track with python, which is 84 hours, and 22 courses in total. It covers the following courses.
Introduction to Python, Intermediate Python for Data Science, Python Data Science Toolbox (Part 1)&(Part 2), Importing Data in Python (Part 1) & (Part 2), Cleaning Data in Python, pandas Foundations, Manipulating DataFrames with pandas, Merging DataFrames with pandas, Intro to SQL for Data Science, Introduction to Databases in Python, Introduction to Data Visualization with Python, Interactive Data Visualization with Bokeh, Statistical Thinking in Python (Part 1) & (Part 2), Joining Data in SQL, Supervised Learning with scikit-learn, Machine Learning with the Experts: School Budgets, Unsupervised Learning in Python, Deep Learning in Python, Network Analysis in Python (Part 1)
What do I like about the datacamp?
1- There are very well-designed practice sections after the video content.
2- Topic explains from a different expert that they are professional data scientist working at industry or in the universities.
3- Topic content start with basic ideas and then evolving so, it helps the understanding process especially for the machine learning part.
4- There are a lot of additional courses apart from career track or skill track.
5-There are also course covered case studies especially for the machine learning part.
6- They are continuing to adding new courses.
7- There are datasets for every course that you can make practice own your own.
What I don’t like about the datacamp?
1- R programming courses more than python programming courses. 😒
2- Sometimes the provided datasets are different than in the videos or the practice part. So, you can see the different result or you may need additional effort on the datasets the bring the same result.
3- Even if all technical part well-covered but I think I need more practice to be more efficient. For example, in the data cleaning part I got every technical detail but if I got a really messy dataset I am not sure how to handle the data.
4- I understand the idea of data science part by part. I think there are not good at putting the piece of information together to going through the whole process. Like, How I connect the SQL and Python?
What do I differently if just start the course?
At the beginning of the course I want to reach the machine learning part so, I did faster the first part of the course and I didn’t practice using the provided-datasets. Using the datasets and going through all process by oneself it improving a lot. Before jump into the next course, I should probably make more practice by myself.
Did it worth it? Should you take the course?
It is totally worth it… I paid the $99 for a year (there was a deal) and I even did not complete my year yet. I believe it is good to start your data science journey. You can try their free courses it could help decide what should you take the course or not. I totally tump up for the datacamp. Happy Coding everyone.
