Data Science Training

[Pre-work for those without experience in Python]

• Get introduced to Python key concepts and libraries - Pandas.
• Explore conditional programming through Python functions like, ‘if’, ‘loops’, ‘in’ and ‘not’.
• Automate repetitive tasks and create a data transformation pipeline by learning how to loop using dictionaries elements.
• Learn how to use object-oriented-programming with classes, objects, attributes, methods and inheritance.

• Explore your first datasets using Pandas, the de facto Python library for data manipulation. 

• Clean, wrangle and curate multiple data sets in a fast and efficient way. 

• Characterize your dataset with descriptive statistics and uncover trends and relationships.

• Use probabilities and statistics to answer questions and test hypotheses to help make informed decisions.

• Understand Machine Learning use cases by first solving classification & regression problems.

• Build, train and evaluate your first ML models and be aware of overfitting and underfitting. 

• Use distance-based algorithms to solve classification problems and unsupervised tasks.

• Develop Machine Learning models, and compare them.

• Make a time series analysis and predict the future through forecasting models.

• Learn how to build a compelling narrative to share your insights to stakeholders.

• Build your first dashboards using Dash and set up automatic reporting emails to stakeholders.  

• Act as the AI team of a start-up: your model will dictate if the business thrives or fails. Deploy your first model to the cloud.

• Build the automation tools to monitor how the model is performing and communicate insights.

• Update your Resume with all your learnings throughout the course

• Position yourself as a Data Scientist by optimizing your Linkedin profile and showcasing your program credentials and projects 

• Distinguish yourself with an online project portfolio with all the relevant challenges of the program

• Prepare for technical interview processes and nail down your pitch