Advanced Data Science Certification

The Knowledge Academy is Globally Recognised as the Industry Leader in providing Data Science Training courses to professionals and organisations. Our ‘Data Scientists Expert Team’ has 16 years of experience dealing with massive amounts of data using cutting-edge tools and techniques to uncover previously unseen patterns, generate meaningful information, and make business decisions. Our trainers have developed unmatchable teaching methods to equip trainees with knowledge and skills required in the development of complex machine learning algorithms for building predictive models across the entire data science pipeline.

Most Demanded Job Roles in Data Field

Increase in the Demand of Data Scientists in 2022

47.1%

Increase in the Demand of Data Analysts in 2022

27.9%

Increase in the Demand of AI and Machine Learning in 2022

40%

Data Science Course Overview

Data Science refers to the process of extracting valuable information from various structured or unstructured data, e.g., data mining. Data Science aims to explore, sort, and analyse metadata from a variety of sources and use them to draw conclusions, optimise business processes, and support decision-making. Our industry experts have developed the Advanced Data Science Certification to help individuals know how Data Science works and how it plays an important role in Artificial Intelligence (AI). Our experienced trainer will conduct interactive training sessions to help learners become successful Data Scientists and improve their ability to analyse business data to extract meaningful insights.

Advanced Data Science Certification

All Delivery Methods Available: Yes

Modules of Data Science Certification

Data Science is a multidisciplinary mixture of algorithm development, data interference, and technology to solve analytically complex problems. For building programming knowledge and analytical skills with Data Science course, you should learn the below topics:

Module Module Module Module Module Module Module

Python for Data Analysis - NumPy

Introduction to NumPy
NumPy Arrays
Aggregations
Computation on Arrays: Broadcasting
Fancy Indexing
Sorting Arrays
NumPy’s Structured Arrays

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

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

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

Machine Learning

Introduction
Importance
Types
Working
Machine Learning Mathematics

Natural Language Processing

Introduction
NLP Example
Advantages
NLP Applications

Deep Learning

Introduction
Importance
Working

Module Module Module Module Module Module

Big Data

Big Data Analytics
State of Practice in Analytics
Main Roles for New Big Data Ecosystem
Phases of Data Analytics Lifecycle0

Working with Data in R

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

Regression in R

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

Modelling Data in Power BI

Power BI Data Model
What are the Relationships?
Viewing Relationships
Creating Relationships
Cardinality

Shaping and Combining Data Using Power BI

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

Interactive Data Visualisations

Page Layout and Formatting
Multiple Visualisation
Creating Charts
Using Geographic Data
Histograms

Capstone Projects

For skilled and highly experienced professionals, Data Science is the most promising and in-demand career path. So, accelerate your career by attending our Advanced Data Science Certification. Have a look at the capstone projects included:

Retrieve, Process, and Visualise Data with Python and R
Machine Learning Applications in Different Sectors
Product-Sales Analysis using Power BI

Delivery Methods

Classroom Training

Online Instructor-Led Training

Online Self-Paced Training

Onsite Training

Essential Data Science Skills

A Data Scientist is a professional responsible for gathering, analysing, and interpreting massive amount of data. The skill set of a data scientist is a combination of computer science, statistics, and mathematics. They analyse, process, and model data before analysing the collected data to develop actionable plans for businesses and other organisations. Data Scientists work with different functional teams to implement models and monitor results. However, technical abilities are not the only consideration. They are frequently found in business settings, where they are responsible for communicating complex ideas and making data-driven organisational decisions. As a result, they must be effective communicators, leaders, team members, and high-level analytical thinkers.

How Data Science Works?

Data Science is the field that deals with huge amounts of data using modern techniques in order to identify and uncover insights, extract meaningful information, and make better business decisions. Data for analysis comes from various resources and is presented in different formats and works in five distinctive stages, each of which has its own tasks, such as:

Capture- Data Entry, Data Acquisition, and Data Extraction
Maintain- Data Cleansing, Data Warehousing, and Data Processing
Process- Clustering, Data Mining, Data Summarisation and Modelling
Analyse- Predictive Analysis, Regression, and Qualitative Analysis
Communicate- Data Visualisation, Business Intelligence, and Decision Making

Data Science Process

Data Science is a systematic process that data scientists use to analyse, visualise, model, and transform enormous volumes of data into actionable insights in a methodical way. Below given is the process of Data Science:

Business Understanding

Data Understanding

Data Preparation

Model Building

Evaluating Model

Model Deployment

Reasons to Count on Us

We help you quench your thirst for knowledge by providing you with our specially tailored certifications. Our highly qualified instructors, dedicated staff, and 24/7 available helpline are the main reasons why we're the go-to training provider for you.

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Guaranteed to Run

Our training courses are 100% guaranteed to run on dates provided, whether they are classroom, virtual, or in-house.

Highly Experienced Staff

Our support staff and instructors have years of experience in meeting the specific needs of our clients and delivering exceptional quality.

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What Roles can be played after attending Data Science and Artificial Intelligence Training?

Data Scientist

Data Engineer and Data Analyst

Al Engineer and Scientist

Analytics and Insights Analyst

Applied Scientist

Junior Data Scientist

AI and ML Engineer

Difference Between Data Science and Data Analytics

What Our Clients Say About Us

I purchased the advanced data science certification course from the knowledge academy. They had well-qualified and experienced trainers who ran the course sequentially by maintaining a smooth flow. The course material was fully understandable and approachable and covered every essential topic. I will recommend the knowledge academy to my friends for such a great experience of learning.

Eveline Fernandez

Data Scientist

I recently completed expert data science programme from the knowledge academy. The session was very interactive and informative. Tutor was very friendly and clarified each query in detail. The course content was very useful and I would definitely recommend Henrik and the knowledge academy to those looking to deep dive into data science and gain advanced skills. I am very grateful to this academy.

Amelia Cruze

Data Engineer

The knowledge academy provided me with a great learning experience through its data science expert programme. Instructor conducted the session in a smooth flow and clarified every concept. His superb knowledge and experience brought the subject alive through meaningful examples and useful discussions, ensuring we were all able to relate to each topic and reflect on our own practice.

Henry Willow

Business Analyst

Last week, I did advanced data science certification course and had Kevin as the teacher. His suitable examples were incredibly engaging and interesting, but also relatable, and helped to contextualise the theory and how it applies in the real world. He explained theory in a way that made it sound more exciting. The pace was not too fast or too slow and content was covered in sufficient time every day of the course.

Jack Hector

Data Analyst

From the knowledge academy, I enjoyed expert data science certification course that assisted me with the use of modern techniques to analyse operational behaviour. The course material was well designed and covered every advanced concept that is required to get placed in this respective field. I had a very positive experience with the trainer, who was quite nice and answered all my queries.

Ella Saffron

Junior Data Scientist

I have just completed expert data science programme from the knowledge academy. The course was very good, useful, and well organised. The tutor’s knowledge and enthusiasm regarding the subject matter made this a very satisfactory experience. He informed us various techniques to master each question. I will use knowledge academy again and recommend it to my colleagues as well.

Mesila Fern

Machine Learning Engineer

My trainer, Kelly, facilitated an advanced data science course at the knowledge academy and had superb excellent knowledge of the subject around business data management. She was excellent at articulating these experiences into relatable examples using the methodologies within the course. Along with the smooth delivery of the course, it made the learning experience all that much easier.

Samuel Darcy

Data Architect

Hendrick has been an amazing trainer. He made the curriculum easy and interesting so that it's easy for us to follow and remember while preparing. He had also shared handful of materials to refer and get all the required knowledge about data science. He was very patient and clarifies all your queries with a big smile.

John Robert

Applied Scientist

Frequently Asked Questions

What is data visualisation in Data Science?

In Data Science, data visualisation is a graphical description of data and information. With the help of graphs and charts (visual components), data visualisation tools give a convenient method to view and follow trends, data patterns and outliers.

What is the data wrangling process?

The process of selecting, gathering, and transforming data to answer an analytic question is known as data wrangling, and it is also known as data cleaning or munging.

What skills are needed to be a Data Scientist professional?

Statistics, programming language, data extraction, data wrangling and exploration, machine learning algorithms, data visualisation and many more are the skills needed to become a Data Scientist professional.

What will I learn in this Data Science training?

During the Data Science training, you will learn various concepts such as how data science works, difference between data science and data analytics, essential data science skills, including capstones etc.

Can you customise training material according to our company requirements?

Yes, we have subject matter experts who will work according to your company requirements.

Do You Have Any Query?

Not fully sure which is the right course for you? Or want to make sure that you choose the right course? Just Contact Us. We are always here to assist our prospective learners and clients.

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