Data and AI online courses recommended by Sertizens!

During Working from Home, you may feel demotivated due to the lack of socialising. You might miss hanging out or sitting with your colleagues. However, one benefit of WFH is that you get more time in your life. Let’s make the most of this time.

According to the Future of Jobs report from World Economic Forum, the highest demanding job in the future is Data Analyst, followed by AI and Machine learning experts. The rest of the ranking is mostly tech careers.

Then, shouldn’t we upskill ourselves with these hottest data and AI skills? Sertis is presenting data and AI online course recommendations, guaranteed by Sertizens who have completed them and found them very useful that they wanted to share. Don’t miss such an insightful recommendation from tech people. Utilise your time by enrolling on these courses to unlock the potential in you.

Find the course(s) that suits you best and if you need more recommendations on any field, feel free to leave a comment down below.

1. Go: The Complete Developer’s Guide (Golang) from Udemy

This course is about ‘Go’ — a famous programming language developed by Google. We will get a chance to learn Go from the basics and dig into more advanced features. You will be ready to write your own program before you know it.

“I recommend Go: the complete developer guide course. The instructor taught me from zero knowledge to build simple applications. Also, Go is one of the programming languages that is used for building back-end applications.”, said Oeuf, Software Engineer

2. Become a Data Engineer from Udacity

Let’s move to the data engineering field. This Data Engineering course recommended by Brook, Data Engineer, is suitable for those who have intermediate knowledge of Python and SQL, and want to develop to be a professional data engineer.

Brook explained that “This course started from laying the foundation of data engineering to providing the advanced knowledge that is practical for projects in our company. It also has a capstone project that gives us hands-on experience of practising on AWS cloud. This course covers all the processes, from how to input data, store data in the data warehouse (Redshift) and Data Lake, to the detailed how-to of ETL tool (Airflow).”

3. Deep Learning Specialization from Coursera

This Deep Learning Specialization course covers aspects of deep learning, another class of machine learning. This course covers the topics of how to build and train kinds of neural networks. It provides a good foundation for those who wish to be AI experts.

Aish, Senior Data Scientist, and Aubin, Senior AI researcher, both recommended this course.

“The professor is really good, he goes in-depth when required but also gives a good high-level understanding for those who don’t understand machine learning in-depth.”

She also added that “His course is mostly on neural networks, which are quite complicated, but if people wanna learn more basic models and the logic behind them, then I also like to watch this youtube channel called StatQuest. This guy makes it super easy to understand complicated models.”

Aubin also confirmed that this course is useful. He added a recommendation on reading that, “As for the reading recommendation, ‘Pattern Recognition and Machine Learning’ by Christopher Bishop is a must.”

4. Probabilistic Graphical Models Specialization from Coursera

This course is designed to help learners master the foundations of Probabilistic Graphical Models. The content covers a variety of concepts, including probability theory, graph algorithms, machine learning, etc.

Ankush, Senior AI Researcher, told us that, “It’s an advanced-level course that assumes a good mathematical understanding, especially in probability distributions, multivariate calculus, and graph data structures. I took this course to better understand the process of inference, both exact and approximate, and parameter estimation in both directed and undirected graphical models. Professor Koller’s lectures, aided with the reading materials and the programming assignments, make this course a must for keen data scientists.”

5. Machine Learning by Coursera

This Machine Learning course provides an introduction to machine learning, data mining, and statistical pattern recognition. It is a good start for those who want to open the door to machine learning careers.

Nat, Data Scientist, told us that, “This course provides a good foundation for people who aim to understand the principles of machine learning. Personally, I got the job here at Sertis from this course.”

He also explained the pros and cons of the course. “The pros are that the lecturer can simplify the complex issue by not compromising with the details. The homework is well constructed and helps the understanding process. While the con is that the programming language used in this course is octave which you may use only once with the course.”

6. Data Literacy Fundamentals by DataCamp

This course is recommended by our Data Analysts, Tuck and Chalee. This course focuses on providing fundamental skills to explore the world of data and get to know several data topics — data science, machine learning, data visualization, and even data engineering and cloud computing.

Tuck recommended that “For beginners or potential learners, overall, I think it is understandable. it provides a general understanding of data projects. Some parts of them are quite technical, but you may find some specific content on Datacamp to learn more if you are interested.”

Chalee also said that “I recommend this skill track for someone who wants to work in a data company and wants to be able to communicate with all technical teams fluently. It gives learners keywords and buzzwords in the data world and provides a basic theory behind algorithms.”

7. Data Engineering for Everyone from DataCamp

Our Associate Data Engineer, Tangkwa, recommended this course. This course lays the foundations for those whose dream job is a data engineer. It covers the core responsibilities and skills of a data engineer.

“It helps me to understand more of the task of a data engineer. I think that this course is very suitable for starting this job because it explains the importance of this job and the basic skills that should be. Otherwise, it helps explain more about the difference between a data scientist and data engineer that many people confuse about this.”, said Tangkwa

8. Design Thinking from TUXSA

This Design Thinking course helps learners build a ground for developing their design thinking. This way of thinking is beneficial when you have to generate fresh ideas or solve complex problems. Outwardly, this course may not seem to link to data careers, but actually, it helps.

“It is not much about data, but it can help a lot about our way of thinking when we need to find insight from something that we are not familiar with. It helps you ask the good questions to find out something, think out of the box, improve your storytelling, and make insight more insightful.”, said Mgnum, our Senior Data Analyst.

Written by Sertis

Leading big data and AI-powered solution company