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Bootcamp in Data Science

High quality teaching

There are many online courses available today. Many of them lack the ability to help you translate your knowledge into something physical and the ability to excel and grow as a Data Science professional. We have designed this course to meet this challenge by giving you the academic rigor, learning support, and peer communication of a Bootcamp with the flexibility of an online program.

A unique component of the program is integrating a comprehensive curriculum covering the industry’s most widely used tools and techniques alongside a hands-on learning approach. A structured learning journey will help you stay on track while achieving your weekly learning milestones with your mentor and benefit from their professional experience.

We know it’s essential to consider your future career before coming on board this course. This Data Science course will develop your analytical and critical skills while also providing you with the tools and competencies you need to integrate numerical, textual and qualitative data logically.

These include extracting significance from basic information and presenting the results of their examinations and their implications to stakeholders or managers. The skills you will learn can lead to careers with small and large technological firms, the biomedical sector, the public sector and the voluntary and charitable sector.

This Bootcamp will teach you the skills required to explain and critically assess machine learning and statistical data mining techniques. You will also be able to evaluate emerging data analysis technologies and analyse in-depth how data analysis techniques can be applied.

About The Program

There are many online courses available today. Many of them lack the ability to help you translate your knowledge into something physical and the ability to excel and grow as a Data Science professional. We have designed this course to meet this challenge by giving you the academic rigor, learning support, and peer communication of a Bootcamp with the flexibility of an online program. A unique component of the program is integrating a comprehensive curriculum covering the industry’s most widely used tools and techniques alongside a hands-on learning approach. A structured learning journey will help you stay on track while achieving your weekly learning milestones with your mentor and benefit from their professional experience.

Take your career to the next level

We know it’s essential to consider your future career before coming on board this course. This course in Data Science will develop analytical and critical skills while also providing you with the tools and competencies you need to integrate numerical, textual and qualitative data logically. These include extracting significance from basic information and presenting the results of their examinations and their implications to stakeholders or managers.

The skills you will learn can lead to careers with small and large technological firms, the biomedical sector, the public sector and the voluntary and charitable sector.

This course will teach you the skills required to explain and critically assess machine learning and statistical data mining techniques. You will also be able to evaluate emerging data analysis technologies critically and analyse in-depth how data analysis techniques can be applied

Online Data Science Become, 56 hours over 16 weeks

Cromwell College Bootcamp is complete Data Science Training: that includes Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning.

This Bootcamp contains a complete curriculum covering the industry’s most widely-used tools and techniques with a hands-on learning approach. An expert tutor delivers this Bootcamp in Data Science and business analytics through adapted Bootcamp sessions, hands-on projects, and career support. An organized learning approach keeps you on track throughout your journey with your tutor while benefiting from their long-standing professional expertise.

The program offers you the opportunity to apply your skills and knowledge in real-time every week through interactive mentor-led practice sessions, quizzes, assignments, and hands-on projects.

You’ll be added to our WhatsApp group for Q and A and continuous professional development support and problem-solving

Course Description

The Solution   

Data science is a multidisciplinary field. It encompasses a wide range of topics.   

  • Understanding of the data science field and the type of analysis carried out  
  • Mathematics  
  • Statistics   
  • Python   
  • Applying advanced statistical techniques in Python   
  • Data Visualization  
  • Machine Learning  
  • Deep Learning  

Each of these topics builds on the previous ones. And you risk getting lost along the way if you don’t acquire these skills in the right order. For example, one would struggle in the application of Machine Learning techniques before understanding the underlying Mathematics. Or, it can be overwhelming to study regression analysis in Python before knowing what a regression is.    

We believe this is the first training program that solves the biggest challenge to entering the data science field – having all the necessary resources in one place.  

Moreover, our focus is to teach topics that flow smoothly and complement each other. The course teaches you everything you need to know to become a data scientist at a fraction of the cost of traditional programs (not to mention the amount of time you will save).   

The Skills

  1. Introduction to Data and Data Science

 Big data, business intelligence, business analytics, machine learning, and artificial intelligence. We know these buzzwords belong to the field of data science but what do they all mean?     

Why learn it? As a candidate data scientist, you must understand the ins and outs of each of these areas and recognise the appropriate approach to solving a problem. This ‘Introduction to data and data science’ will give you a comprehensive look at all these buzzwords and where they fit in the realm of data science. 

  1. Mathematics

Learning the tools is the first step to doing data science. You must first see the big picture to examine the parts in detail.   

We take a detailed look specifically at calculus and linear algebra as they are the subfields data science relies on.   

Why learn it?  

Calculus and linear algebra are essential for programming in data science. If you want to understand advanced machine learning algorithms, then you need these skills in your arsenal.

  1. Statistics

You need to think like a scientist before you can become a scientist. Statistics trains your mind to frame problems as hypotheses and gives you techniques to test these hypotheses, just like a scientist.  

Why learn it?  

This course doesn’t just give you the tools you need but teaches you how to use them. Statistics trains you to think like a scientist.

  1. Python

Python is a relatively new programming language and, unlike R, it is a general-purpose programming language. You can do anything with it! Web applications, computer games, and data science are among many of its capabilities. That’s why it has managed to disrupt many disciplines in a short space of time. Extremely powerful libraries have been developed to enable data manipulation, transformation, and visualisation. Where Python shines is when it deals with machine and deep learning.

Why learn it?   

When it comes to developing, implementing, and deploying machine learning models through powerful frameworks such as scikit-learn, TensorFlow, etc, Python is a must have programming language.  

  1. Tableau

Data scientists don’t just need to deal with data and solve data-driven problems. They also need to convince company executives of the right decisions to make. These executives may not be well versed in data science, so the data scientist must be able to present and visualise the data’s story in a way they will understand. That’s where Tableau comes in, and we will help you become an expert story teller using the leading visualisation software in business intelligence and data science.

 Why learn it?   

A data scientist relies on business intelligence tools like Tableau to communicate complex results to non-technical decision-makers.  

  1. Advanced Statistics

Regressions, clustering, and factor analysis are all disciplines that were invented before machine learning. However, these statistical methods are performed through machine learning to provide predictions with unparalleled accuracy. This section will look at these techniques in detail.  

 Why learn it?  

Data science is all about predictive modelling, and you can become an expert in these methods through this ‘advanced statistics’ section.  

  1. Machine Learning

The final part of the program and what every section has been leading up to is deep learning. Being able to employ machine and deep learning in their work often separates a data scientist from a data analyst. This section covers all common machine learning techniques and deep learning methods with TensorFlow.  

  Why learn it?   

Machine learning is everywhere. Companies like Facebook, Google, and Amazon have been using machines that can learn on their own for years. Now is the time for you to control the machines.  

 ***What you get***

  • A data science training program   
  • Active Q&A support  
  • All the knowledge to get hired as a data scientist  
  • A certificate of completion   
  • Solve real-life business cases that will get you the job   

You will become a data scientist from scratch. 

Who this course is for:

  • You should take this course if you want to become a Data Scientist or if you want to learn about the field
  • This course is for you if you want a great career
  • The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skill
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