BIG DATA SKILLSTREE

Micro Skill

you

IS1 BD
Introduction to Data Science
HS1 BD
Programming Language (Python)
HS2 BD
SQL for Data Analytics
HS6 BD

Data Visualization with Power BI

HS7 BD

Knowledge of CRM / Database

HS8 BD

ETL or Extract Transform and Load

Junior Data Scientist
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BIG DATA SKILLSTREE

you

Micro skills

IS1 BD
Introduction to Data Science
HS1 BD
Programming Language (Python)
HS2 BD
SQL for Data Analytics
HS6 BD

Data Visualization with Power BI

HS7 BD
Knowledge of CRM / Database
HS8 BD
ETL or Extract Transform and Load
Junior Data Scientist
Discover More
Go

Average Compensation

for Junior Data Scientist

Monthly

$5,000 to

$8,333

Annual

$60,000 to

$100,00

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& unlock your future!

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Micro Learning

  • Basic understanding of:
  • Data mining
  • Mathematics for data science
  • Python programming
  • Machine Learning
  • Data Analysis
  • Data visualisation
  • Decision-making
  • Basic of Artificial Intelligence and Python
  • Data Analysis with Python
  • Python for beginners
  •  Programming Language (Python) Pyt
  • hon / JAVA (Hadoop) – Files and Directories
  •  Python Sequences
  • Image Class
  • ification using Python Chatbot: by ChatGPT with Python
    > Cloud Computing -Python – File IO
  • Basic of SQL Learning
  •  Effective use of Joins
  • Using Subqueries
  •  Excel to mySQL / Analytic Techniques
  •  Data Wrangling

Part 1: Pre-Requisite Skills Learning before taking Power BI:

  • Microsoft Excel (Basic / Beginner)
  • Microsoft Excel – Fundamental Data Type and Function for Data Analysing
  • Microsoft Excel – Functions, Cell Reference & Range Name
  • Microsoft Excel (Intermediate)
  • Microsoft Excel Function and Formula
  • Microsoft Excel (Automate and Protect Workbooks)
  • Microsoft Excel (Pivot Table)
  • Microsoft Excel (Advanced)

Part 2: Tool Usage: Power BI Learning

  • Learn Power BI in 2 hours
  • Tool application learning (Introductory)
  • Introduction to Data Storage and Formats
  •  Data storage options: HDFS, cloud storage, NoSQL databases (MongoDB)
  • Common data formats: JSON, Parquet, Avro.
  • Trade-offs between storage formats
  • MongoDB Deployment
  • Introduction to  Data Extract, transform, and load (ETL)
  •  Workflow and Process methods: Batch and Real-time reporting (Power Automate)
  • Data Quality and Transformation
  • Data storage and management