Getting Started

Introductory Intermediate Advanced Projects Intern Activities

Coursera Account

Please, open a Coursera account at www.coursera.org . Some topics in our syllabus are based on free lectures at Coursera. Coursera sometimes provides you an online platform to run Python codes, but it is limited to specific courses only. You may need special instruction to enroll for free. Coursera also provides a specialization ( for example Deep Learning Specialization) in the specific topics. If you are not paying for certificates, you can freely enroll individual courses in the specialization.

EDX Account

Please, open an edX account at www.edx.org . Some topics in our syllabus are based on free lectures at edX. You may need special instruction to enroll for free. EdX also provides a specialization in the specific topics ( for example Data Science and Engineering with Spark XSeries Program). If you are not paying for certificates, you can freely enroll in individual courses in the specialization.

Udacity Account

Please, open a Udacity account at www.udacity.com . Some topics in our syllabus are based on free lectures at Udacity. You may need special instruction to enroll it for free. Udacity also provides nano dgrees in different topics for example Machine Learning, Deep Learning, AI, Robotics, Blockchain etc. Some of the courses included in nano degrees are freely available.

Google Collaboratory

If you already have a google account, you can use Google Collaboratory to run Python codes. Collaboratory has already preinstalled python packages like scikit-learn, tensorflow, pandas, numpy, etc. Google's Collaboratory is available at www.colab.research.google.com . Best way to use Google Collaboratory is by keeping all your Python Notebooks at Goole Drive where you can open directly in the browser using Collaboratory Chrom extension.

Github Account

Please, open a GitHub account at www.github.com , if you don't have one yet. Github will facilitate us to track versions of our code and group work. We will host our projects at GitHub repo so that participants from different places could participate. You can work with Github support either by (1) command line from terminals, or (2) using the desktop app, or (3) from the browser. You can also create data visualization demo at GitHub using HTML/CSS and javascript. The web app you are currently reading is also hosted at GitHub.

Kaggle Account

Please, open a Kaggle account at www.kaggle.com If you dont have one yet. At Kaggle, you can run your python codes as well as participate in data science compitition. One Benefit from kaggle is that you can learn latest trend in Machine Laearning and Data Science by experts participating in Kaggle competition. We can work on a specific Data Science Competition once you reach to the expert level .

Databricks Account

Please, open an account at Databricks Community Edition available at www.databricks.com . At Community Edition you can run your Spark codes with Jupyter notebooks. Spark is one of the best BigData tool in the market. For beginners, this is the best place to start with Spark. Spark can be used with MangoDB, SQL database and Neo4j.

Slack Account

Please, accept our invitation to Slack workspace for group discussion available at Invitation Link . If you get any problem regarding our syllabus and projects, we will try to be available for instructions. Sometimes it is hard to communicate with large mass using Gmail because such email communication my go to spam class. So we think, Slack is the best way to communicate for now. You are welcome to our SLACK team!