Advanced Analytics (2018)

Data Science & Advanced Analytics Code.Learn Program_Weekly Schedule-Learning Outcomes

Duration

• This specific Code.Learn program lasts 3 weeks (3 Fridays, 3 Saturdays) with 36 hours of lectures and hands-on exercise on a real life project.

Key Objectives – Curriculum

This program will present, explore and adequately cover with extended hands-on sessions & real-life case studies the following areas

• Introduction to Python & Jupyter
  – Basics (conditions; iterations etc)
  – Data types & Data structures
• Data Manipulation & Analysis
  – Principles & Techniques
  – Numpy
  – Scipy
  – Pandas
  – Exploratory Data Analysis
• Data Visualization
  – Principles & Necessity (Anscombe’s quartet)
  – Matplotlib
  – Seaborn
  – Charts, Plots & Advanced options
• Machine Learning
  – Introduction, algorithms, solutions & business problems standpoint
  – Supervised Learning with scikit-learn
  – Advanced ML concepts (data imputation, cross-validation and others)
  – Unsupervised Learning
• Real-life ML problem
  – Problem statement & Business perspective
  – Data inspection
  – EDA
  – Data Manipulation
  – Data Modeling

Target Audience

Data analysts, data scientists, data engineers, BI engineers/developers, information-visualization-analytics professionals as well as computer scientists, software engineers, developers and consultants who vision their future in data-relevant career paths are welcome to participate to this code.learn program and unlock the full potentiality of the topics taught by upskilling their  future career.