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Suggested Age: 14 to 16 Years

Introduction:

This course equips learners with the essential skills/knowledge of a data scientist which include data collection, cleanup, transformation, analysis, and visualization. Learners will write algorithms, tell data stories, and build statistical models using Python libraries. They will use the same tools that data scientists use to draw meaningful insights and solve organizational problems. This course is highly visual, dynamic, and interactive, and engaging

Prerequisites:

Some knowledge of programming (not language specific) and an interest in computer science.

What is covered in this course?

A: The Data Science Life Cycle

The Data Science Life Cycle Learners will learn and apply the process of the data science life cycle. This includes asking statistical questions, collecting or obtaining reliable raw data, analysing the data using measures of central tendency and spread and interpreting and summa.

  • What is Data Science?
  • Gathering Data
  • Exploring Data Using Python
  • Modules, Packages & Libraries
  • Series and Central Tendency
  • Measures of Spread
  • Pandas DataFrames
  • Selecting Columns
  • Using Functions
  • Mini-Project: Findings
  • The Data Science Life Cycle Quiz
  • Quizzes
  • Assignments/Projects 

B: Data Science for Change

Learners will use and analyse data to better understand a problem, measure the scope of a problem, or understand how people are affected by the problem. They will learn more about cleaning a dataset and filtering by column, rows, and conditions.

  • Data Science for Change
  • Big Data and Bias
  • Importing and Filtering Data
  • Conditional Filtering
  • Data Cleaning
  • Exploring with Visualizations
  • Interpret and Present
  • Quizzes
  • Assignments/Projects

Please write us email for full course details.

Hands-on experience:

Learners write and run Python programs in the browser using the (CodeHS text editor).

Modes of Course Delivery & Attendance:

ITPT is currently providing different method of learning opportunities to our learners. We have made available diverse and flexible learning methods to accommodate a wider variety of learners.

Modes of Course Delivery      Modes of Attendance
  1. Face to Face (F2F) Classroom based Tutor-Led learning
  1. Boot Camps / Fast track
  1. Virtual learning (VL) Tutor-Led learning
  1. Weekends

 

  1. Blended Learning (BL) – (Combination of F2F + VL)

 

  1. Weekdays

Target Audience:

This course is suitable to a wide range of learners including;

  • Learners interested in learning new Emerging Technology
  • Learners who wish to enhance Data Science knowledge
  • Learners who wish to study on a fast track learning mode during holidays
  • Learners who wish to upgrade in their existing fundamental knowledge

Other info (Starting Date, Cost & Duration):

Start & Ending Date Days Duration Class Timings Cost
TBC TBC TBC TBC TBC

The above cost is for Face to Face and virtual delivery, for eLearning’s please contact us at info@itpt.co.uk.

 

    (Which training centre you looking for admission – Edinburgh)