1. Use Python and SQL to access and analyse data from several different data sources.
2. Build predictive models using a variety of unsupervised and supervised machine learning techniques.
3. Perform feature engineering to improve the performance of machine learning models.
4. Optimize, tune, and improve algorithms according to specific metrics like accuracy and speed.
5. Compare the performances of learned models using suitable metrics.

Assessment

Project completion

Certification

• Learners will be awarded Certificate of Completion co-issued by TP and Udacity in Introduction to Machine Learning with TensorFlow upon completion of at least ONE project.
   
• Learners will be awarded the Nanodegree conferred by Udacity in Introduction to Machine Learning with TensorFlow upon completion of ALL projects.