Advanced Data Science Certification

The Advanced Data Science Certification course provides professionals with advanced knowledge of data science methodologies, tools, and techniques. It focuses on machine learning, data analysis, and predictive modeling to solve complex business problems and drive innovation.

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Overview

The Advanced Data Science Certification course is designed for professionals seeking to deepen their expertise in data science. This advanced-level course equips learners with in-depth knowledge of data analysis, machine learning, and predictive modeling techniques, enabling them to extract meaningful insights and make data-driven decisions effectively.

Data science is transforming industries by empowering organisations to harness the power of big data. This course covers key topics such as advanced statistical methods, machine learning algorithms, data visualization, and real-world applications of data science in solving complex business challenges.

This 4-day training course offered by MPES includes expert-led sessions, hands-on exercises, and real-world case studies. Learners will gain practical experience in using data science tools and frameworks, developing predictive models, and implementing machine learning solutions. Upon completion, learners will earn the Advanced Data Science Certification, showcasing their expertise in this high-demand field.

Course Objectives

Understand advanced data science principles and methodologies
Develop skills in predictive modeling and machine learning algorithms
Learn to visualise and communicate data insights effectively
Gain expertise in leveraging data for strategic decision-making
Prepare comprehensively for the Advanced Data Science Certification

Upon completion, learners will have the knowledge and skills to apply advanced data science techniques in professional settings, driving innovation and solving complex business problems.

Average completion time

4 Month

with unlimited support

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Course Includes

Course Details

Develop your understanding of essential financial, business and management accounting techniques with ACCA Applied Knowledge. You'll learn basic business and management principles and the skills required of an accountant working in business.

Entry Requirements

Educational Background: A foundational understanding of data science or related fields is recommended. A background in mathematics, statistics, or programming will be beneficial.
Technical Proficiency: Familiarity with data analysis tools and programming languages like Python or R is advantageous.
Interest in Advanced Analytics: Ideal for professionals aiming to enhance their skills in data science, machine learning, and predictive analytics.

Learning Outcomes

Master Advanced Data Science Concepts: Gain in-depth knowledge of methodologies and frameworks for data analysis.
Develop Machine Learning Expertise: Learn to design, train, and evaluate machine learning models for real-world applications.
Visualise and Interpret Data: Build proficiency in creating visualizations and communicating data-driven insights effectively.
Implement Predictive Models: Gain skills to develop and deploy predictive analytics solutions.

Target Audience

The Advanced Data Science Certification course is tailored for professionals seeking to advance their expertise in data science. It equips learners with advanced tools and techniques for solving complex problems and making data-driven decisions effectively. Below are the individuals who will benefit from this course:

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

Course content

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 Direaction
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

MPES Support That Helps You Succeed

At MPES, we offer comprehensive support to help you succeed in your studies. With expert guidance and valuable resources, we help you stay on track throughout your course.

MPES Learning offers dedicated support to help you succeed in Accounting and Finance courses.
Get expert guidance from tutors available online to assist with your studies.
Check your eligibility for exemptions with the relevant professional body before starting.
Our supportive team is here to offer study advice and support throughout your course.
Access a range of materials to help enhance your learning experience. These resources include practice exercises and additional reading to support your progress.

Career Growth Stories

Discover how MPES Learning transforms careers with real success stories.

George Evans

The Financial Risk Management Course at MPES was invaluable in deepening my understanding of risk assessment and mitigation strategies. The hands-on learning approach allowed me to apply new concepts directly to my work. I highly recommend it for professionals in finance.

George Evans

Risk Manager

James Robinson

As a financial consultant, I am always seeking ways to enhance my expertise. The Investment Analysis Course at MPES exceeded my expectations, offering practical skills and knowledge that I can apply immediately in my consulting work. It's an outstanding choice for professionals in finance.

James Robinson

Financial Consultant

Laura Bennett

The Corporate Finance Course I attended at MPES was transformative. The depth of knowledge shared by the instructors and the relevance of the topics covered have directly impacted on our financial strategy. I strongly endorse this program for anyone in a leadership position in finance.

Laura Bennett

Chief Financial Officer

Emma Johnson

The Financial Modeling and Valuation Course at MPES was incredibly insightful. The practical applications and real-world examples helped solidify my understanding of complex concepts. I highly recommend this course to anyone looking to enhance their financial acumen.

Emma Johnson

Financial Analyst

Arvy Pasanting

As a qualified accountant, studying at MPES has been a very rewarding experience. Its team of passionate and dedicated mentors gave me the confidence and knowledge I needed to not just excel at my current role as an auditor, but also inspired me to expand my horizons.

Arvy Pasanting

Audit Senior (incoming Reconciliations Manager)

David Ford

I was recommended MPES after searching for a way to pursue a career in the accounting profession, I have studied with them throughout my journey utilising both their “in class” and online learning opportunities that fit around the needs of my employer, I have found them to be consummate professionals delivering first class accounting courses with support always available.

David Ford

Accountant

Aaron Allcote

As a finance officer, MPES has been a huge help in understanding the process of recording and processing transactions from all different perspectives. The courses are very easy to follow, and the training they provide can be applied to real-life scenarios. The courses have been a huge help for me, and I would highly recommend them.

Aaron Allcote

Finance Officer

Bob Beaumont

I completed all of my ACA studies with MPES and I think you would struggle to find a better training provider anywhere in the British Isles. MPES' tutors are excellent both at delivering training and giving individualised feedback and coaching. the supporting materials and the out of class support are also great.

Bob Beaumont

Senior Accountant

George Evans

George Evans

Risk Manager

James Robinson

James Robinson

Financial Consultant

Laura Bennett

Laura Bennett

Chief Financial Officer

Emma Johnson

Emma Johnson

Financial Analyst

Arvy Pasanting

Arvy Pasanting

Audit Senior (incoming Reconciliations Manager)

David Ford

David Ford

Accountant

Aaron Allcote

Aaron Allcote

Finance Officer

Bob Beaumont

Bob Beaumont

Senior Accountant

Have Questions? We’ve Got You

If you have any questions, we’re here to help. Find the answers you need in the MPES detailed FAQ section.

Q. Do I need prior experience in data science to take this course?

Yes, a foundational understanding of data science or related fields is recommended. Familiarity with programming and data analysis tools will be helpful.

Q. What topics are covered in this course?

The course includes advanced statistical analysis, machine learning algorithms, predictive modeling, data visualisation, and real-world applications of data science in solving business challenges.

Q. How is the course delivered?

The course is delivered through expert-led sessions, hands-on exercises, and case studies to provide practical experience and real-world application of advanced data science concepts.

Q. Who should take this course?

This course is ideal for data scientists, analysts, machine learning engineers, and professionals looking to enhance their skills in advanced analytics and predictive modeling.

Q. Will I receive a certification upon completing this course?

Yes, learners will receive the Advanced Data Science Certification, validating their expertise and skills in advanced data science methodologies and applications.

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Resources

Access a wide range of free resources to support your learning journey. From blogs to news and podcasts, these valuable guides are available at no cost to help you succeed.

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