Data Analyst to Data Scientist

R12 789.00

This course takes you along four tracks towards progressing from Data Analyst to Data Scientist: Data Analyst, Data Wrangler, Data Ops and Data Science.

Online books Digital learning
Clock Start anytime
Study duration (Months)
Computer Skillsoft LMS access
Teacher and student Online Skillsoft mentor
Certificate Certified by Optimi College

Course code: C01081

 

Subjects:

Data Science Track 1: Data Analyst

Data Engineering Fundamentals
Python for Data Science: Introduction to NumPy for Multi-dimensional Data
Python for Data Science: Advanced Operations with NumPy Arrays
Python for Data Science: Introduction to Pandas
Python for Data Science: Manipulating and Analyzing Data in Pandas DataFrames
R for Data Science: Data Structures
R for Data Science: Importing and Exporting Data
R for Data Science: Data Exploration
R for Data Science: Regression Methods
R for Data Science: Classification & Clustering
Data Science Statistics: Simple Descriptive Statistics
Data Science Statistics: Common Approaches to Sampling Data
Data Science Statistics: Inferential Statistics
Accessing Data with Spark: An Introduction to Spark
Getting Started with Hadoop: Fundamentals & MapReduce
Getting Started with Hadoop: Developing a Basic MapReduce Application Hadoop HDFS: Introduction
Hadoop HDFS: Introduction to the Shell
Hadoop HDFS: Working with Files
Hadoop HDFS: File Permissions
Data Silos, Lakes, & Streams: Introduction
Data Silos, Lakes, and Streams: Data Lakes on AWS
Data Silos, Lakes, & Streams: Sources, Visualizations, & ETL Operations
Data Analysis Application
Analyzing Data with Python (Lab)
Final Exam: Data Analyst
Mentoring Data Science Journey Data Architecture Primer

Data Science Track 2: Data Wrangler

Mentoring Data Science Journey
Data Wrangling with Pandas: Working with Series & Data
Frames Data Wrangling with Pandas: Visualizations and Time-Series Data
Data Wrangling with Pandas: Advanced Features
Data Wrangler 4: Cleaning Data in R
Data Tools: Technology Landscape & Tools for Data Management
Data Tools: Machine Learning & Deep Learning in the Cloud
Trifacta for Data Wrangling: Wrangling Data
MongoDB for Data Wrangling: Querying
MongoDB for Data Wrangling: Aggregation
Getting Started with Hive: Introduction
Getting Started with Hive: Loading and Querying Data
Getting Started with Hive: Viewing and Querying Complex Data
Getting Started with Hive: Optimizing Query Executions
Getting Started with Hive: Optimizing Query Executions with Partitioning
Getting Started with Hive: Bucketing & Window Functions
Getting Started with Hadoop: Filtering Data Using MapReduce
Getting Started with Hadoop: MapReduce Applications With Combiners
Getting Started with Hadoop: Advanced Operations Using MapReduce
Accessing Data with Spark: Data Analysis Using the Spark DataFrame API
Accessing Data with Spark: Data Analysis using Spark SQL
Data Lake: Framework & Design Implementation
Data Lake: Architectures & Data Management Principles
Data Architecture – Deep Dive: Design & Implementation
Data Architecture – Deep Dive: Microservices & Serverless Computing
Final Exam: Data Wrangler
Data Wrangling with Python (Lab)

Data Science Track 3: Data Ops

Deploying Data Tools: Data Science Tools
Delivering Dashboards: Management Patterns Delivering Dashboards: Exploration & Analytics
Cloud Data Architecture: DevOps & Containerization Compliance
Issues and Strategies: Data Compliance Implementing Governance Strategies
Data Access & Governance Policies: Data Access Oversight and IAM
Data Access & Governance Policies: Data Classification, Encryption, and Monitoring
Streaming Data Architectures: An Introduction to Streaming Data
Streaming Data Architectures: Processing Streaming Data
Scalable Data Architectures: Introduction
Scalable Data Architectures: Introduction to Amazon Redshift
Scalable Data Architectures: Working with Amazon Redshift & Quick Sight Building Data Pipelines
Data Pipeline: Process Implementation Using Tableau & AWS
Data Pipeline: Using Frameworks for Advanced Data Management
Data Sources: Integration
Data Sources: Implementing Edge on the Cloud Securing Big Data Streams
Harnessing Data Volume & Velocity: Big Data to Smart Data
Data Rollbacks: Transaction Rollbacks & Their Impact
Data Rollbacks: Transaction Management & Rollbacks in NoSQL
Implementing Data Ops with Python (Lab)
Final Exam: Data Ops
Mentoring Data Science Journey

Data Science Track 4: Data Scientist

Balancing the Four Vs of Data: The Four Vs of Data
Data Driven Organizations
Raw Data to Insights: Data Ingestion & Statistical Analysis
Raw Data to Insights: Data Management & Decision Making
Tableau Desktop: Real Time Dashboards
Storytelling with Data: Introduction
Storytelling with Data: Tableau & PowerBI
Python for Data Science: Basic Data Visualization Using Seaborn
Python for Data Science: Advanced Data Visualization Using Seaborn
Data Science Statistics: Using Python to Compute & Visualize Statistics
R for Data Science: Data Visualization
Advanced Visualizations & Dashboards: Visualization Using Python
Advanced Visualizations & Dashboards: Visualization Using R
Powering Recommendation Engines: Recommendation Engines
Data Insights, Anomalies, & Verification: Handling Anomalies
Data Insights, Anomalies, & Verification: Machine Learning & Visualization Tools
Data Science Statistics: Applied Inferential Statistics
Data Research Techniques
Data Research Exploration Techniques
Data Research Statistical Approaches
Machine & Deep Learning Algorithms: Introduction
Machine & Deep Learning Algorithms: Regression & Clustering
Machine & Deep Learning Algorithms: Data Preperation in Pandas ML
Machine & Deep Learning Algorithms: Imbalanced Datasets Using Pandas ML
Creating Data APIs Using Node.js
Data Visualization with Python (Lab)
Final Exam: Data Scientist
Mentoring Data Science Journey

The ability to read and write in English.

Learners must be at least 16 years of age.

Course type: Short course

Certification: Certificate confirming course completion.

Certification issued by: Optimi College

Online assessments

Course fee: R12 789.00

Deposit: R2 200.65

Monthly instalment: R882.42

Payment duration: 12 months

Study duration: You will have course access for 12 months. To complete the course, we recommend a total of 200 hours of study, e.g. study 1 hour per day and complete your course in 7 months.

Dedicated support team

Online Skillsoft mentor

Skillsoft Learner Management System (LMS) access

Skillsoft app access

Skillsoft practice labs (online)