Education
Technology
Data Science
Online Courses
Machine Learning
Online Learning
Python Programming
Here are the list of courses i took when i started learning data science and machine learning last year
1. Complete data science and machine learning bootcamp from Zero to mastery. udemy.com
1. Complete data science and machine learning bootcamp from Zero to mastery. udemy.com
The very first day i took this data science bootcamp, i was hooked, they made me fall in love with machine learning and data science and i haven't looked back since then. The beautiful thing about this course is you get to add 3 projects to your portfolio to showcase to employers
Another thing about the data science bootcamp is they get to teach you python from scratch, so you don't need to have prior python knowledge or know anything about data science or ML, you will learn the basics from this course and build from there when you build projects
2. Statistics is the backbone of data science and understanding inferential and descriptive statistics will help you make inference and have an understanding of your data. This course will arm you with statistics knowledge coursera.org
3. If you want to follow the data analyst path, this course is for you. One reason why i took this course is because i wanted to have an understanding of how data analysts work and the various tools a data analyst needs when working with data coursera.org
4. The difference between the IBM data analyst course and google data analytics course is IBM teaches data analysis with Python and google teaches data analysis with R, the courses are similar, Whichever course you want to take is up to you really. coursera.org
5. I also took this machine learning foundations free course on udacity because i wanted to understand how ML algorithms work when i fit the model to my data and i'm trying to build predictive machine learning projects. udacity.com
6. There are lots of free courses you can take on udacity if you want to have a foundational understanding on certain concepts be it in data science/machine learning, cloud engineering etc . You can find the courses here udacity.com
7. I also took this intro to deep learning with pytorch because machine learning/deep learning is the area i am particularly interested in and building advanced deep learning models be it NLP, CV models etc is what i intend to specialize in udacity.com
8. It is important to note that while you are taking courses on data analytics, data science, machine learning etc. You don't get stuck in the web of just taking online courses and not applying it by doing projects. Doing personal projects are what reaffirms your python skills
You can get datasets to work on from kaggle.com, zindi.com, data.gov, archive.ics.uci.edu and a whole hosts of websites that are one google search away.
I regularly participate on hackathons on zindi because instead of working with sample datasets, zindi provides real datasets from companies that want ML solutions for their business problems and you can win money if you win the competition, the same applies to kaggle
While i am still taking courses and doing more projects to gain knowledge and build my portfolio, it is imperative to state that the data science journey is a marathon and not a sprint, the learning never stops really.
So if things aren't going your way, don't worry, keep pushing, keep learning, keep doing projects, keep improving your skills and keep applying to those tech roles you want, you will eventually get the job, i know i don't have my dream job for now but i will soonπ
I will keep updating this thread as i take more courses.
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I forgot to add that one of the skills you will need as a data analyst/scientist is to be able to properly visualize data and tell a compelling story, you will need to learn either tableau or power bi for that and udacity offers a free tableau course udacity.com
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