This is a comprehensive four-track sequence, developed as the Skillsoft Aspire Learning Journey for Data Science. The tracks include:
Track 1 – Data Analyst – Focused on legacy DBs, mixed and siloed data sources, Excel tricks. Covers data science applications of Python, R, Statistics, Hadoop, Spark. HDFS, Data Silos, Data Streams and Data Lakes and more.
Track 2 – Data Wrangler – Focused on normalization, cleaning, structuring, automation and transformation of data. Covers Data Wrangling w/ Python/Pandas, MongoDB for Data Wrangling, Cleaning Data in R, Data Lakes in Practice, Building Data Pipelines, Accessing Data with Spark, Getting Started with Hive.
Track 3 – Data Ops – Focus on real-time pipelines, governance, scaling and backup strategy, security and integration. Covers Streaming Data Architectures, Scaling Data Architectures, Enterprise Governance Strategies, Secure Data Sources from the Edge, Data Rollbacks, Governance Policies and Access and more.
Track 4 – Data Scientist – Focus on Insights, Knowledge, Verifiable, Veracity, Scientific Approach, Communication and Visualization. Covers Raw Data to Insights, Data Pipeline to Tableau, Creating RT Dashboards, Powering Recommend Engines, Advanced Architectures, ML & DL Algorithms, Storytelling with Data and more.
Includes Two Bonus Tracks:
Track 5 – Business and Leadership Skills for Data Science
Track 6 – Productivity and Collaboration Tools for Data Science