Since Canada enjoys an elite education system, you can have more opportunities here than any other place. Canada is home to several great universities such as Saint Mary's University, Carleton University, Seneca College, Trent University, University of British Columbia, Simon Fraser University etc. These institutes offer prominent courses in data science -
Here is the skill set you need to become a Data Scientist in Canada:
If you want to become a master Data Scientist, you need to have a thorough understanding of at least one analytical tool. Knowledge of R programming helps in solving any data science problem easily.
One of the most popular languages used in Data Science, Python is simple and versatile. It can take various data formats and help in data processing. It also aids the data scientists in creating and performing operations on a dataset.
SQL is a database language that helps the data scientists in accessing, communicating and working on the data. This helps in gaining insights into the formation and structure of a Database. MySQL is another such language that has concise commands that significantly reduce the technical skills required for performing operations on a database.
Apache Spark is one of the most popular data sharing technologies. It is a big data computation technology like Hadoop, only it is better. The other difference is that Spark makes cache of its computations in the system memory while Hadoop reads and writes to the disk.
Apache Spark helps data science algorithms run faster. It also prevents loss of data along with help in disseminating the data processing of a large dataset. Spark also can handle the complex unstructured datasets easily. The speed with which it operates helps the data scientist carry out the project more quickly.
Although it is not a requirement, it is preferred by various data science projects. A study done on LinkedIn proved that for becoming a data science engineer, Hadoop was a leading skill requirement.
Data Scientists work with unstructured data which is not labelled and organized into database values. This unstructured data include videos, blog posts, audio samples, social media posts, customer reviews, etc.
- Machine Learning and Artificial Intelligence
If you want to pursue a career in the field of Data Science, you need to be proficient in Machine Learning and Artificial Intelligence. Following are the concepts that you need to make yourself familiar with:
- Neural Network
- Decision tree
- Reinforcement Learning
- Logistic regression
- Adversarial learning
- Machine learning algorithms, etc.
- Data Visualization
Visualization tools like ggplot, d3.js, matplotlib, and Tableau are used to help the data scientist visualize the data. After the processes are performed on a dataset and converted into complex results, this result is converted into a format that is easy to understand. Data Scientists work with data directly and grasp insights from this data. This will also help them to act on the outcomes.