Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learninga
What you'll
learn
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The course provides the entire toolbox you need to become a data
scientist
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Fill up your resume with in demand data science skills:
Statistical analysis, Python programming with NumPy, pandas, matplotlib, and
Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats
models and scikit-learn, Deep learning with TensorFlow
·
Impress interviewers by showing an understanding of the data
science field
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Learn how to pre-process data
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Understand the mathematics behind Machine Learning (an absolute
must which other courses don’t teach!)
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Start coding in Python and learn how to use it for statistical
analysis
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Perform linear and logistic regressions in Python
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Carry out cluster and factor analysis
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Be able to create Machine Learning algorithms in Python, using
NumPy, statsmodels and scikit-learn
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Apply your skills to real-life business cases
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Use state-of-the-art Deep Learning frameworks such as Google’s
TensorFlowDevelop a business intuition while coding and solving tasks with big
data
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Unfold the power of deep neural networks
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Improve Machine Learning algorithms by studying underfitting,
overfitting, training, validation, n-fold cross validation, testing, and how
hyperparameters could improve performance
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Warm up your fingers as you will be eager to apply everything
you have learned here to more and more real-life situations
Show less
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No prior experience is required. We will start from the very
basics
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You’ll need to install Anaconda. We will show you how to do that
step by step
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Microsoft Excel 2003, 2010, 2013, 2016, or 365
Description
The Problem
Data scientist is one of the best suited
professions to thrive this century. It is digital, programming-oriented, and
analytical. Therefore, it comes as no surprise that the demand for data
scientists has been surging in the job marketplace.
However, supply has been very limited. It is
difficult to acquire the skills necessary to be hired as a data scientist.
And how can you do that?
Universities have been slow at creating
specialized data science programs. (not to mention that the ones that exist are
very expensive and time consuming)
Most online courses focus on a specific topic
and it is difficult to understand how the skill they teach fit in the complete
picture
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.
So, in an effort to create the most effective,
time-efficient, and structured data science training available online, we
created The Data Science Course 2021.
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. Intro 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 ‘Intro 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.
2. Mathematics
Learning the tools is the first step to doing
data science. You must first see the big picture to then 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.
3. 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.
4. 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, in a short space of time, it has
managed to disrupt many disciplines. Extremely powerful libraries have been
developed to enable data manipulation, transformation, and visualisation. Where
Python really shines however, 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.
5. 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 but 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.
6. Advanced Statistics
Regressions, clustering, and factor analysis
are all disciplines that were invented before machine learning. However, now
these statistical methods are all 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 ‘advance statistics’
section.
7. 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 is what 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 $1250 data science training
program
- Active Q&A support
- All the knowledge to get hired
as a data scientist
- A community of data science
learners
- A certificate of completion
- Access to future updates
- Solve real-life business cases
that will get you the job
You will become a data scientist from scratch
We are happy to offer an unconditional 30-day
money back in full guarantee. No risk for you. The content of the course is
excellent, and this is a no-brainer for us, as we are certain you will love it.
Why wait? Every day is a missed opportunity.
Click the “Buy Now” button and become a part
of our data scientist program today.
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
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This course is for you if you want a great career
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The course is also ideal for beginners, as it starts from the
fundamentals and gradually builds up your sk
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