Python Certification Training for Data Science

Access Duration - 365 Days
4.3( 3 REVIEWS )

What Will I Learn?

Learn techniques to deal with different types of data – ordinal, categorical, encoding
Learn how to use I python notebooks, master the art of presenting step by step data analysis
Gain insight into the 'Roles' played by a Machine Learning Engineer
Learn tools and techniques for predictive modelling
Gain expertise to handle business in future, living the present


Ever wanted to work for a tech giant like Google or Facebook? Python could be your way in, as these companies, as well as YouTube, IBM, Yahoo, Dropbox, Quora, Mozilla, Instagram, and many others all use Python for a wide array of purposes, and are constantly hiring Python developers. Having Python under your belt can help you land a job in very short terms. What’s more, the demand for Python skills clearly outstrips jobseeker interest. The job market outlook for Python developers is excellent at the moment.

One significant advantage of learning Python is that it’s a general-purpose language that can be applied in a large variety of projects. Python’s application in data science and data engineering is what’s really fuelling its popularity today. Pandas, NumPy, SciPy, and other tools combined with the ability to prototype quickly and then “glue” systems together enable data engineers to maintain high efficiency when using Python.

Why You Should Consider Taking this Course at Global Edulink?

Global Edulink is a leading online provider for several accrediting bodies, and provides learners the opportunity to take this exclusive course awarded by CPD. At Global Edulink, we give our fullest attention to our learners’ needs and ensure they have the necessary information required to proceed with the Course.  Learners who register will be given excellent support, discounts for future purchases and be eligible for a TOTUM Discount card and Student ID card with amazing offers and access to retail stores, the library, cinemas, gym memberships and their favourite restaurants.

  • Access Duration
  • Who is this Course for?
  • Entry Requirement
  • Method of Assessment
  • Certification
  • Awarding Body
  • Career Path & Progression
The course will be delivered directly to you, and from the date you joined the course you have 12 months of access to the online learning platform. The course is self-paced, and you can complete it in stages at any time.
  • Programmers, Developers, Technical Leads, Architects, Freshers
  • Business Analysts
  • Data Scientists, Data Analysts
  • Statisticians and Analysts
  • Project Managers
  • Learners should be over the age of 16, and have a basic understanding of English, ICT and numeracy.
  • A basic understanding of Computer Programming Languages.
In order to complete the course successfully, learners will take an online assessment. This online test is marked automatically, so you will receive an instant grade and know whether you have passed the course.

Upon the successful completion of the course, you will be awarded the ‘Python Certification Training for Data Science’ by CPD.

CPD is an internationally recognised qualification that will make your CV standout and encourage employers to see your motivation at expanding your skills and knowledge in an enterprise.

Once you successfully complete the course, you will gain an accredited qualification that will prove your skills and expertise in the subject matter. With this qualification you can further expand your knowledge by studying related courses on this subject, or you can go onto get a promotion or salary increment in your current job role. Below given are few of the jobs this certificate will help you in, along with the average UK salary per annum according to

  • Computer Programmer - Up to £30;per annum
  • Software Engineer - Up to £32k per annum
  • Net Programmer – Up to £30k per annum
  • Software Developer - Up to £24k per annum

Key Features

Gain an Accredited UK Qualification
Access to Excellent Quality Study Materials
Personalised Learning Experience
Support by Phone, Live Chat, and Email
Eligible for TOTUM Discount Card
UK Register of Learning Providers Reg No : 10053842

Course Curriculum

1: Introduction to Python
Overview of Python
The Companies using Python
Different Applications where Python is used
Discuss Python Scripts on UNIX/Windows
Values, Types, Variables
Operands and Expressions
Conditional Statements
Command Line Arguments
Writing to the screen
2: Sequences and File Operations
Python files I/O Functions
Strings and related operations
Tuples and related operations
Lists and related operations
Dictionaries and related operations
Sets and related operations
3: Deep Dive – Functions, OOPs, Modules, Errors and Exceptions
Function Parameters
Global Variables
Variable Scope and Returning Values
Lambda Functions
Object-Oriented Concepts
Standard Libraries
Modules Used in Python
The Import Statements
Module Search Path
Package Installation Ways
Errors and Exception Handling
Handling Multiple Exceptions
4: Introduction to NumPy, Pandas and Matplotlib
NumPy – arrays
Operations on arrays
Indexing slicing and iterating
Reading and writing arrays on files
Pandas – data structures & index operations
Reading and Writing data from Excel/CSV formats into Pandas
matplotlib library
Grids, axes, plots
Markers, colours, fonts and styling
Types of plots – bar graphs, pie charts, histograms
Contour plots
5: Data Manipulation
Basic Functionalities of a data object
Merging of Data objects
Concatenation of data objects
Types of Joins on data objects
Exploring a Dataset
Analysing a dataset
6: Introduction to Machine Learning with Python
Python Revision (numpy, Pandas, scikit learn, matplotlib)
What is Machine Learning?
Machine Learning Use-Cases
Machine Learning Process Flow
Linear regression
Gradient descent
7: Supervised Learning - I
What are Classification and its use cases?
What is Decision Tree?
Algorithm for Decision Tree Induction
Creating a Perfect Decision Tree
Confusion Matrix
What is Random Forest?
8: Dimensionality Reduction
Introduction to Dimensionality
Why Dimensionality Reduction
Factor Analysis
Scaling dimensional model
9: Supervised Learning - II
hat is Naïve Bayes?
How Naïve Bayes works?
Implementing Naïve Bayes Classifier
What is Support Vector Machine?
Illustrate how Support Vector Machine works?
Hyperparameter Optimization
Grid Search vs Random Search
Implementation of Support Vector Machine for Classification
10: Unsupervised Learning
What is Clustering & its Use Cases?
What is K-means Clustering?
How does K-means algorithm work?
How to do optimal clustering
What is Hierarchical Clustering?
How Hierarchical Clustering works?
11: Association Rules Mining and Recommendation Systems
What are Association Rules?
Association Rule Parameters
Calculating Association Rule Parameters
Recommendation Engines
How does Recommendation Engines work?
Collaborative Filtering
Content-Based Filtering
12: Reinforcement Learning
What is Reinforcement Learning
Why Reinforcement Learning
Elements of Reinforcement Learning
Exploration vs Exploitation dilemma
Epsilon Greedy Algorithm
Markov Decision Process (MDP)
Q values and V values
Q – Learning
α values
13: Time Series Analysis
What is Time Series Analysis?
Importance of TSA
Components of TSA
White Noise
AR model
MA model
ARMA model
ARIMA model
14: Model Selection and Boosting
What is Model Selection?
The need for Model Selection
What is Boosting?
How Boosting Algorithms work?
Types of Boosting Algorithms
Adaptive Boosting

Students feedback


Average rating (3)
5 Star
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1 Star
    A M

    Alexia May

    January 20, 2021

    The course covered even more things that i was expected. I was able to gain in-depth knowledge of Python and you will also get familiarity with data structures.

    A C

    Amiyah Clark

    December 01, 2020
    Helpful modules

    I like the modules because they are helpful to test if I really learnt and if not go back and check where I didn’t understand.

    E K

    Esmee Knight

    November 13, 2020

    Very good stuff for the new learners and each concept is explained in a detailed manner. Keep up the good work.

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