Advanced Data Science Certification - Canada

Advanced Data Science Certification​ Course Outline

Module 1: Python for Data Analysis - NumPy

• Introduction to NumPy
• NumPy Arrays
• Aggregations
• Computation on Arrays: Broadcasting
• Comparison, Boolean Logic and Masks
• Fancy Indexing
• Sorting Arrays
• NumPy’s Structured Arrays

Module 2: Python for Data Analysis – Pandas

• Installing Pandas
• Pandas Objects
• Data Indexing and Selection
• Operating on Data in Pandas
• Handling Missing Data
• Hierarchical Indexing
• Concat and Append
• Merge and Join
• Aggregations and Grouping
• Pivot Tables
• Vectorised String Operations
• Working with Time Series
• Eval() and Query()

Module 3: Python for Data Visualisation – Matplotlib

• Overview
• Object-Oriented Interface
• Two interfaces
• Simple Line Plots and Scatter Plots
• Visualising Errors
• Contour Plots
• Histograms, Binnings and Density
• Customising Plot Legends
• Customising Colour Bars
• Multiple Subplots
• Text Annotation
• Three-Dimensional Plotting

Module 4: Python for Data Visualisation – Seaborn

• Installing Seaborn and Load Dataset
• Plot the Distribution
• Regression Analysis
• Basic Aesthetic Themes and Styles
• Distinguish between Scatter Plots, Hexbin Plots and KDE Plots
• Use Boxplots and Violin Plots
• Compare the Use Cases of Swarn Plots, Bar Plots Strip Plots, and Categorical Plots
• Recall Some of the Use Cases and Features of Seaborn

Module 5: Machine Learning

• Introduction
• Importance
• Types
• How Does Machine Learning Works?
• Machine Learning Mathematics

Module 6: Natural Language Processing

• Introduction to NLP
• NLP and Writing Systems
• Advantages
• NLP Applications

Module 7: Deep Learning

• Introduction
• Importance
• Working

Module 8: Big Data

• Big Data Analytics
• State of Practice in Analytics
• Main Roles for New Big Data Ecosystem
• Phases of Data Analytics Lifecycle

Module 9: Working with Data in R

• Data Manipulation in R
• Data Clean Up
• Reading and Exporting Data
• Importing Data
• Charts and Graphs

Module 10: Regression in R

• Regression Analysis
• Linear Regression
• Logistic Regression
• Multiple Regression
• Normal Distribution
• Binomial Distribution

Module 11: Modelling Data

• What are the Relationships?
• Viewing Relationships
• Creating Relationships
• Cardinality
• Cross Filter Direction
• What is DAX?
• Syntax
• Functions
• Row Context
• Calculated Columns
• Calculated Tables
• Measures

Module 12: Shaping and Combining Data using Power BI

• Query Editor
• Shaping Data and Applied Steps
• Advanced Editor
• Formatting Data
• Transforming Data
• Combining Data

Module 13: Interactive Data Visualisations

• Page Layout and Formatting
• Multiple Visualisation
• Creating Charts
• Using Geographic Data
• Histograms
• Power BI Admin Portal
• Service Settings
• Desktop Settings
• Dashboard and Report Settings

Who Should Attend this Advanced Data Science Certification Course?

This Advanced Data Science Certification Course is tailored for individuals seeking to enhance their expertise in the field of data science. This training is particularly beneficial for professionals such as:

• Experienced Data Analysts
• Data Scientists
• Machine Learning Engineers
• Statisticians
• Business Analysts
• AI Developers
• Entrepreneurs
• Researchers

Prerequisites of the Advanced Data Science Certification Course

There are no formal prerequisites for the Advanced Data Science Certification Course. However, having prior knowledge of multiple programming languages will be beneficial for the delegates.

Advanced Data Science Certification Course Overview

Advanced Data Science Training introduces delegates to key concepts that underpin modern data-driven practice. It explains how techniques such as numerical computing, regression, and machine learning mathematics enable deeper analysis and informed decision-making across complex datasets.

This Advanced Data Science Training supports professionals seeking to strengthen advanced analytical capability. It builds the ability to identify patterns, interpret data accurately, and drive innovation, enabling confident contribution in data-focused and strategic roles across industries.

This 4-Day course offered by The Knowledge Academy enables delegates to apply advanced data science concepts with confidence. Delegates gain the skills to work with time series, visualise data, manage analytics lifecycles, and operate at an expert level.

Advanced Data Science Certification Course Objectives

• To provide a comprehensive understanding of basic and advanced data science concepts
• To equip delegates with practical skills in tools such as Pandas and Power BI
• To cover critical topics like NumPy arrays, regression analysis, and Machine Learning mathematics
• To empower Business Analysts, Data Engineers, Software Developers, and executives with data science proficiency
• To enable delegates to unravel complex patterns and make informed decisions through data-driven insights
• To ensure delegates emerge as adept Data Scientists capable of tackling real-world data challenges

Upon completion of this Data Science Certification training, delegates will not only possess a solid foundation in data science but also practical skills in tools like Pandas and Power BI. This empowers them to analyse data effectively, make informed decisions, and contribute meaningfully to their organisations' success.

What’s Included in this Advanced Data Science Certification Course?

• World-Class Training Sessions from Experienced Instructors
• Advanced Data Science Certificate
• Digital Delegate Pack

You’ll also get access to the MyTKA Training Portal, which will be your go to hub for all your training.
Hands-On Labs: Included as part of our online instructor-led delivery, these labs provide real-world exercises in a simulated environment guided by expert instructors to enhance your practical skills.