Tuesday, 11 February 2020
Monday, 10 February 2020
Finally! A complete guide on how to get a job in football!
When most of us think of jobs within the football (soccer) industry, the list is usually exhausted after the players, officials and coaching team. But behind the scenes are the inner-workings of one of the fastest-growing industries in the world comprising a vast array of careers that keep the beautiful game ticking.
If you are interested in getting management or operational roles within the football industry, you have a difficult job ahead. Football management careers can indeed pay very well, however, getting your career started and becoming successful can turn out to be more difficult than you think.
Saam Momen is the creator of this course and has worked at reputable sport marketing agencies and at the heart of the European football (UEFA) and knows what it really takes to succeed in the industry. He has condensed years of knowledge together with some extensive study, research and conversation with other experts and turned it into an all-inclusive, informative guide.
With women and girls becoming more interested and involved in all aspects of football, employment opportunities are increasingly available for them in what has been a male dominant environment. This online course is targeted at both genders and the opportunities described within are available for males and females. However, there is a specific module where additional opportunities for women and girls can be found.
This course intends to break down all of the difficulties mentioned previously into practical steps you can take immediately and start to focus your career into the right direction. This is a rare opportunity to get your football management career started (or back on track), connect and access the best opportunities in the football industry, and get insights amongst other things of industry-recognised institutions providing educational degrees in football and sports management.
Here are the key areas this course will be covering:
Networking is one of the essential tools for growth in any career and football is no exception. However, the rules are slightly different when it comes to football management. During the course you will learn how to locate the right networking environments within the football industry and how to seize the opportunities when you are faced with them.
With Saam’s experience and extensive connection within the sports industry, he will introduce you to what is considered arguably the best football and sports job fair in Europe. This is a unique occasion to be face to face with the recruitment departments of the best football entities in the world, an opportunity not to be missed.
A comparison of interviews for ‘normal’ jobs and those for jobs in the football industry will be found in this course. A look at the interview formats involved, the skill set that you should display, the questions you may be asked and the questions that you can be asking your prospective employer will also be provided.
Women in football
Women and girls have long faced bias and discrimination that has seen a low representation at the top of the sport. These days, however, women are finding increasing opportunities to succeed in the football industry. We will discuss here the events, organisations and courses which help to increase the diversity and impact of women in football around the world.
Saam will be sharing with you some of the best career websites which in some cases host head-hunters focused on the football industry. Here you will also find a guide with over 500 job websites for men's and women's football in Europe.
If you want to pursue an undergraduate degree in sports/football management and you don’t know which colleges/universities to apply to, information will be shared about some of the best universities offering undergraduate courses in this area. You can be sure that these are reputable institutions often preferred by sports recruiters.
This is the hardest and at the same time easiest way to secure the job you are looking for in the football industry… and you will find out why in this course!
Continuous education is an important way to stay up to date with career trends in football and sports. Saam will delve into some interesting findings on how you can learn more about the industry from books and podcasts that he will recommend.
Football Seminars
Football Seminars are ideal for networking opportunities. Insights on the best seminars available will be given.
Volunteering
From Saam’s personal experience, this is the best way to start your football management career. He will be sharing recommendations about why, how and where to engage as a volunteer.
One approach to entering into the football industry is to create your own enterprise or startup. Creating a startup can be an effective alternative for some recent graduates or even those who are changing career paths to gain access to the sports industry using their current skills. Insights to the best ways on doing so are given.
Want to learn more in-depth knowledge and how to super charge your sports analytics and technology knowledge? This course will delve into two courses provided by the best universities in the world, Harvard and MIT.
Freelancing
Yes, you can be a freelancer as a sports/football management professional. This course will show you how you can be free to work from anywhere you wish and take up multiple jobs at the same time.
Words from the Author, Saam Momen:
I have a true passion for teaching! I have proudly taught university courses in Switzerland, USA and Brazil. My career spans over 15 years in the sporting industry with jobs at the London Olympic Bid Committee, UEFA, CSM and TEAM Marketing. I possess a Master Degree in Sports Management and an Executive Education diploma at Harvard Business School on The Business of Entertainment, Media and Sports. I hope that throughout this course you are able to have a wonderful learning experience and that ultimately this motivates you to follow your dream path!
Enrol now 100% risk-free since you receive 30 days, unconditional money back guarantee. If for any reason you are not satisfied, no problem, you are one click away from a refund. No hassle, no hard feelings!
Please go ahead and click the “Buy Now” button right now and let’s increase your chances of having a successful career in football!
- Sport management students
- Football executives
- People thinking in changing careers into the football world
- People wanting to learn about the football industry
- Football fans.
52% OFF !!! #discount #udemy #course FOR Finding work in #European #football (soccer)
Finally! A complete guide on how to get your football (soccer) executive career on hi-speed
FREE #soccer #deal #couponcode
https://www.udemy.com/course/finding-work-in-european-football/?couponCode=DA4181203B9CEC2919B7
Friday, 7 February 2020
Core Spatial Data Analysis: Introductory GIS with R and QGIS
Do you find GIS & Spatial Data books & manuals too vague, expensive & not practical and looking for a course that takes you by hand, teaches you all the concepts, and get you started on a real life project?
Or perhaps you want to save time and learn how to automate some of the most common GIS tasks?
I'm very excited you found my spatial data analysis course. My course provides a foundation to carry out PRACTICAL, real-life spatial data analysis tasks in popular and FREE software frameworks.
My name is MINERVA SINGH and i am an Oxford University MPhil (Geography and Environment) graduate. I am currently pursuing a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real life spatial data from different sources and producing publications for international peer reviewed journals.
In this course, actual spatial data from the Tam Dao National Park in Vietnam will be used to give a practical hands-on experience of working with real life spatial data and understanding what kind of questions spatial data can help us answer. The underlying motivation for the course is to ensure you can put spatial data analysis into practice today. Start analyzing spatial data for your own projects, whatever your skill level and IMPRESS your potential employers with an actual example of your spatial data analysis abilities.
This is a core course in spatial data analysis, i.e. we will focus on learning the most important and widely encountered spatial data analysis tasks in both R and QGIS
It is a practical, hands-on course, i.e. we will spend a tiny amount of time dealing with some of the theoretical concepts related to spatial data analysis. However, majority of the course will focus on working with the spatial data from the Tam Dao National Park, Vietnam. After each video you will learn a new concept or technique which you may apply to your own projects.
- Academics
- Researchers
- Conservation managers
- Anybody who works/will work with spatial data.
95% OFF #coupon offer for Spatial #Data #Analysis with R, QGIS & More #udemy #course
https://www.udemy.com/intermediate-spatial-data-analysis-with-r-qgis-more/?couponCode=10PROMO
Spatial Data Analysis With ArcGIS Desktop: Master GIS Techniques and Open Doors to Amazing Geospatial Careers
I WANNA LEARN SPATIAL DATA ANALYSIS, BUT…
- I found most spatial data books & manuals vague
- There are no courses that actually teach me how it’s actually done
- Available resources are expensive & I can’t afford them
- I want to get a job in the field of GIS and geospatial analysis
- I work in the field of ecology or quantitative social sciences or hydrology or civil engineering or geography
Over the past few months, I have published multiple courses on Udemy around this topic which will be tremendously helpful to you & most important of all AFFORDABLE!
Today, I’ve created yet another powerful resource for you!
In this course, over 50+ hands-on and practical lecture, I will help you master the most common and important geo-processing tasks that can be performed with ArcGIS Desktop, one of THE MOST important GIS software tools available.
I will also show you the kind of questions answered through Spatial Analysis & data used.
First of all, we’ll start some basic GIS tasks like “Zooming”.
Then, we’ll move into more complex processing tasks like “Geo-Statistics”.
We’ll also deal with some theoretical concepts related to Spatial Data Analysis, and then we’ll focus on implementing some of the most common GIS techniques (all the way showing you how to execute these tasks in ArcGIS Desktop).
The stuff you’ll learn from this course will be extremely useful in terms of you being able to implement it on future Spatial Data projects you’ll be working on (in a variety of disciplines from ecology to engineering).
My name is MINERVA SINGH.
I am an Oxford University MPhil (Geography and Environment) graduate.
I recently finished my PhD at Cambridge University (Tropical Ecology and Conservation).
I have SEVERAL YEARS OF EXPERIENCE in analyzing REAL LIFE DATA from different sources in ArcGIS Desktop.
I’ve also published my work in many international peer reviewed journals.
My course is a HANDS ON TRAINING with REAL data.
It’s a step by step course covering both the THEORY & APPLICATION of Spatial Data Analysis.
I teach Practical Stuff that you can learn quickly and start implementing NOW.
This is one of the most comprehensive courses on this topic.
I advise you to take advantage of it & enroll in the course TODAY!
Please make sure you have access to ArcGIS before enrolling
- Academics and Researchers
- Conservation managers, field ecologists and social scientists
- People looking to get started in the field of GIS Analysis
- Students of Geography, Environmental Sciences, Geology, Hydrology, Engineering, Earth Sciences and Ecology
- People looking to use ArcGIS Desktop in academic or professional settings.
90% off #udemy #course #ArcGIS #Desktop For #Spatial #Analysis: Go From Basic To Pro!! #couponcode HERE!
https://www.udemy.com/arcgis-desktop-for-spatial-analysis-go-from-basic-to-pro/?couponCode=ARCGIS_PROMO_20
The Fun and Easy Guide to Machine Learning using Keras
Welcome to the Fun and Easy Machine learning Course in Python and Keras.
Are you Intrigued by the field of Machine Learning? Then this course is for you! We will take you on an adventure into the amazing of field Machine Learning. Each section consists of fun and intriguing white board explanations with regards to important concepts in Machine learning as well as practical python labs which you will enhance your comprehension of this vast yet lucrative sub-field of Data Science.
This is a valid question and the answer is simple. This is the ONLY course on Udemy which will get you implementing some of the most common machine learning algorithms on real data in Python. Plus, you will gain exposure to neural networks (using the H2o framework) and some of the most common deep learning algorithms with the Keras package.
We designed this course for anyone who wants to learn the state of the art in Machine learning in a simple and fun way without learning complex math or boring explanations. Each theoretically lecture is uniquely designed using whiteboard animations which can maximize engagement in the lectures and improves knowledge retention. This ensures that you absorb more content than you would traditionally would watching other theoretical videos and or books on this subject.
This is how the course is structured:
- Regression – Linear Regression, Decision Trees, Random Forest Regression,
- Classification – Logistic Regression, K Nearest Neighbors (KNN), Support Vector Machine (SVM) and Naive Bayes,
- Clustering - K-Means, Hierarchical Clustering,
- Association Rule Learning - Apriori, Eclat,
- Dimensionality Reduction - Principle Component Analysis, Linear Discriminant Analysis,
- Neural Networks - Artificial Neural Networks, Convolution Neural Networks, Recurrent Neural Networks.
You DO NOT need any prior Python or Statistics/Machine Learning Knowledge to get Started. The course will start by introducing students to one of the most fundamental statistical data analysis models and its practical implementation in Python- ordinary least squares (OLS) regression. Subsequently some of the most common machine learning regression and classification techniques such as random forests, decision trees and linear discriminant analysis will be covered. In addition to providing a theoretical foundation for these, hands-on practical labs will demonstrate how to implement these in Python. Students will also be introduced to the practical applications of common data mining techniques in Python and gain proficiency in using a powerful Python based framework for machine learning which is Anaconda (Python Distribution). Finally you will get a solid grounding in both Artificial Neural Networks (ANN) and the Keras package for implementing deep learning algorithms such as the Convolution Neural Network (CNN). Deep Learning is an in-demand topic and a knowledge of this will make you more attractive to employers.
Excited Yet?
So as you can see you are going to be learning to build a lot of impressive Machine Learning apps in this 3 hour course. The underlying motivation for the course is to ensure you can apply Python based data science on real data into practice today. Start analyzing data for your own projects, whatever your skill level and IMPRESS your potential employers with an actual examples of your machine learning abilities.
It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to data science. However, majority of the course will focus on implementing different techniques on real data and interpret the results. After each video you will learn a new concept or technique which you may apply to your own projects.
TAKE ACTION TODAY! We will personally support you and ensure your experience with this course is a success. And for any reason you are unhappy with this course, Udemy has a 30 day Money Back Refund Policy, So no questions asked, no quibble and no Risk to you. You got nothing to lose. Click that enroll button and we'll see you in side the course.
- Student who starting out or interested in Machine Learning or Deep Learning.
- Students with Prior Python Programming Exposure Who Want to Use it for Machine Learning
- Students interested in gaining exposure to the Keras library for Deep Learning.
- Data analysts who want to expand into Machine Learning.
- College students who want to start a career in Data Science.
92% discount #coupon #udemy #course for
The Fun and Easy Guide to #Machine #Learning using #Keras
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Learn Data Preprocessing, Data Wrangling and Data Visualisation For Practical Data Science Applications in R
Hello, My name is Minerva Singh. I am an Oxford University MPhil graduate in Geography & Environment & I finished a PhD at Cambridge University in Tropical Ecology & Conservation.
I have +5 of experience in analyzing real-life data from different sources using statistical modelling and producing publications for international peer-reviewed journals. If you find statistics books & manuals too vague, expensive & not practical, then you’re going to love this course!
I created this course to take you by hand and teach you all the concepts, and tackle the most fundamental building block on practical data science - data wrangling and visualisation.
This course is your sure-fire way of acquiring the knowledge and statistical data analysis wrangling and visualisation skills that I acquired from the rigorous training I received at 2 of the best universities in the world, the perusal of numerous books and publishing statistically rich papers in the renowned international journal like PLOS One.
HERE IS WHAT THIS COURSE WILL DO FOR YOU:
- It will take you (even if you have no prior statistical modelling/analysis background) from a basic level of performing some of the most common data wrangling tasks in R.
- It will equip you to use some of the most important R data wrangling and visualisation packages such as dplyr and ggplot2.
- It will Introduce some of the most important data visualisation concepts to you in a practical manner such that you can apply these concepts for practical data analysis and interpretation.
- You will also be able to decide which wrangling and visualisation techniques are best suited to answer your research questions and applicable to your data and interpret the results..
The course will mostly focus on helping you implement different techniques on real-life data such as Olympic and Nobel Prize winners
After each video, you will learn a new concept or technique which you may apply to your own projects immediately! Reinforce your knowledge through practical quizzes and assignments.
- Practice Activities To Reinforce Your Learning
- My Continuous Support To Make Sure You Gain Complete Understanding & Proficiency
- Access To Future Course Updates Free Of Charge
- I’ll Even Go The Extra Mile & Cover Any Topics That Are Related To The Subject That You Need Help With (This is something you can’t get anywhere else).
- & Access To A Community Of 25,000 Data Scientists (& growing) All Learning Together & Helping Each Other!
Now, go ahead & enrol in the course. I’m certain you’ll love it, but in case you don’t, you can always request a refund within 30 days. No hard feelings whatsoever. I look forward to seeing you inside!
- Students Interested In Getting Started With Data Science Applications In The R & R Studio Environment
- Students Interested in Learning About the Common Pre-processing Data Tasks: Including Cleaning and Munging
- Students Interested in Gaining Exposure to Common R Packages Such As ggplot2
- Those Interested in Learning About Different Kinds of Data Visualisations
- Those Interested in Learning to Create Publication Quality Visualisations.
92% discount #coupon #udemy #course for
Complete Data #Wrangling & #Data #Visualisation In R
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Tensorflow and Keras For Neural Networks and Deep Learning
THIS IS A COMPLETE NEURAL NETWORKS & DEEP LEARNING TRAINING WITH TENSORFLOW & KERAS IN PYTHON!
It is a full 7-Hour Python Tensorflow & Keras Neural Network & Deep Learning Boot Camp that will help you learn basic machine learning, neural networks and deep learning using two of the most important Deep Learning frameworks- Tensorflow and Keras.
This course is your complete guide to practical machine & deep learning using the Tensorflow & Keras framework in Python..
This means, this course covers the important aspects of Keras and Tensorflow (Google's powerful Deep Learning framework) and if you take this course, you can do away with taking other courses or buying books on Python Tensorflow and Keras based data science.
In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal and advent of Tensorflow and Keras is revolutionizing Deep Learning...
By gaining proficiency in Keras and and Tensorflow, you can give your company a competitive edge and boost your career to the next level.
But first things first. My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).
I have several years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journals.
Over the course of my research I realized almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic and use data science interchangeably with machine learning..
This gives students an incomplete knowledge of the subject. My course, on the other hand, will give you a robust grounding in all aspects of data science within the Tensorflow framework.
Unlike other Python courses, we dig deep into the statistical modeling features of Tensorflow & Keras and give you a one-of-a-kind grounding in these frameworks!
• A full introduction to Python Data Science and powerful Python driven framework for data science, Anaconda
• Getting started with Jupyter notebooks for implementing data science techniques in Python
• A comprehensive presentation about Tensorflow & Keras installation and a brief introduction to the other Python data science packages
• Brief introduction to the working of Pandas and Numpy
• The basics of the Tensorflow syntax and graphing environment
• The basics of the Keras syntax
• Machine Learning, Supervised Learning, Unsupervised Learning in the Tensorflow & Keras frameworks
• You’ll even discover how to create artificial neural networks and deep learning structures with Tensorflow & Keras
• Getting started with Jupyter notebooks for implementing data science techniques in Python
• A comprehensive presentation about Tensorflow & Keras installation and a brief introduction to the other Python data science packages
• Brief introduction to the working of Pandas and Numpy
• The basics of the Tensorflow syntax and graphing environment
• The basics of the Keras syntax
• Machine Learning, Supervised Learning, Unsupervised Learning in the Tensorflow & Keras frameworks
• You’ll even discover how to create artificial neural networks and deep learning structures with Tensorflow & Keras
You’ll start by absorbing the most valuable Python Tensorflow and Keras basics and techniques.
I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts.
My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement Python based data science in real -life.
After taking this course, you’ll easily use packages like Numpy, Pandas, and Matplotlib to work with real data in Python along with gaining fluency in Tensorflow and Keras. I will even introduce you to deep learning models such as Convolution Neural network (CNN) !!
The underlying motivation for the course is to ensure you can apply Python based data science on real data into practice today, start analyzing data for your own projects whatever your skill level, and impress your potential employers with actual examples of your data science abilities.
This course will take students without a prior Python and/or statistics background background from a basic level to performing some of the most common advanced data science techniques using the powerful Python based Jupyter notebooks
It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to data science. However, majority of the course will focus on implementing different techniques on real data and interpret the results..
After each video you will learn a new concept or technique which you may apply to your own projects!
- People Interested In Learning Python Based Tensorflow and Keras For Data Science Applications
- People With Prior Exposure To Python Programming &/Or Data Science Concepts
- People Interested In Implementing Neural Networks & Deep Learning Models With Tensorflow
- People Interested In Implementing Neural Networks & Deep Learning Models With Keras
92% discount #coupon #udemy #course for
#Tensorflow and Keras For Neural Networks and #Deep #Learning
#couponcode
https://www.udemy.com/tensorflow-and-keras-for-neural-networks-and-deep-learning/
ArcGIS Desktop For Spatial Analysis: Go From Basic To Pro
I WANNA LEARN SPATIAL DATA ANALYSIS, BUT…
- I found most spatial data books & manuals vague
- There are no courses that actually teach me how it’s actually done
- Available resources are expensive & I can’t afford them
- I want to get a job in the field of GIS and geospatial analysis
- I work in the field of ecology or quantitative social sciences or hydrology or civil engineering or geography
Over the past few months, I have published multiple courses on Udemy around this topic which will be tremendously helpful to you & most important of all AFFORDABLE!
Today, I’ve created yet another powerful resource for you!
In this course, over 50+ hands-on and practical lecture, I will help you master the most common and important geo-processing tasks that can be performed with ArcGIS Desktop, one of THE MOST important GIS software tools available.
I will also show you the kind of questions answered through Spatial Analysis & data used.
First of all, we’ll start some basic GIS tasks like “Zooming”.
Then, we’ll move into more complex processing tasks like “Geo-Statistics”.
We’ll also deal with some theoretical concepts related to Spatial Data Analysis, and then we’ll focus on implementing some of the most common GIS techniques (all the way showing you how to execute these tasks in ArcGIS Desktop).
The stuff you’ll learn from this course will be extremely useful in terms of you being able to implement it on future Spatial Data projects you’ll be working on (in a variety of disciplines from ecology to engineering).
My name is MINERVA SINGH.
I am an Oxford University MPhil (Geography and Environment) graduate.
I recently finished my PhD at Cambridge University (Tropical Ecology and Conservation).
I have SEVERAL YEARS OF EXPERIENCE in analyzing REAL LIFE DATA from different sources in ArcGIS Desktop.
I’ve also published my work in many international peer reviewed journals.
My course is a HANDS ON TRAINING with REAL data.
It’s a step by step course covering both the THEORY & APPLICATION of Spatial Data Analysis.
I teach Practical Stuff that you can learn quickly and start implementing NOW.
This is one of the most comprehensive courses on this topic.
I advise you to take advantage of it & enroll in the course TODAY!
Please make sure you have access to ArcGIS before enrolling
- Academics and Researchers
- Conservation managers, field ecologists and social scientists
- People looking to get started in the field of GIS Analysis
- Students of Geography, Environmental Sciences, Geology, Hydrology, Engineering, Earth Sciences and Ecology
- People looking to use ArcGIS Desktop in academic or professional settings.
#ArcGIS Desktop For Spatial Analysis: Go From Basic To Pro #udemy #course 95% off !!! #couponcode
https://www.udemy.com/arcgis-desktop-for-spatial-analysis-go-from-basic-to-pro/?couponCode=ARCGIS10A
Complete Data Science Training with Python for Data Analysis
Complete Guide to Practical Data Science with Python: Learn Statistics, Visualization, Machine Learning & More
THIS IS A COMPLETE DATA SCIENCE TRAINING WITH PYTHON FOR DATA ANALYSIS:
It's A Full 12-Hour Python Data Science BootCamp To Help You Learn Statistical Modelling, Data Visualization, Machine Learning & Basic Deep Learning In Python!
First of all, this course a complete guide to practical data science using Python...
That means, this course covers ALL the aspects of practical data science and if you take this course alone, you can do away with taking other courses or buying books on Python-based data science.
In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal. By storing, filtering, managing, and manipulating data in Python, you can give your company a competitive edge & boost your career to the next level!
But, first things first, My name is MINERVA SINGH and I am an Oxford University MPhil (Geography and Environment), graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).
I have several years of experience in analyzing real-life data from different sources using data science-related techniques and producing publications for international peer-reviewed journals.
Over the course of my research, I realized almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic and use data science interchangeably with machine learning...
This gives the student an incomplete knowledge of the subject. This course will give you a robust grounding in all aspects of data science, from statistical modelling to visualization to machine learning.
Unlike other Python instructors, I dig deep into the statistical modelling features of Python and gives you a one-of-a-kind grounding in Python Data Science!
You will go all the way from carrying out simple visualizations and data explorations to statistical analysis to machine learning to finally implementing simple deep learning-based models using Python
• A full introduction to Python Data Science and powerful Python driven framework for data science, Anaconda
• Getting started with Jupyter notebooks for implementing data science techniques in Python
• A comprehensive presentation about basic analytical tools- Numpy Arrays, Operations, Arithmetic, Equation-solving, Matrices, Vectors, Broadcasting, etc.
• Data Structures and Reading in Pandas, including CSV, Excel, JSON, HTML data
• How to Pre-Process and “Wrangle” your Python data by removing NAs/No data, handling conditional data, grouping by attributes, etc.
• Creating data visualizations like histograms, boxplots, scatterplots, bar plots, pie/line charts, and more!
• Statistical analysis, statistical inference, and the relationships between variables
• Machine Learning, Supervised Learning, Unsupervised Learning in Python
• You’ll even discover how to create artificial neural networks and deep learning structures...& MUCH MORE!
• Getting started with Jupyter notebooks for implementing data science techniques in Python
• A comprehensive presentation about basic analytical tools- Numpy Arrays, Operations, Arithmetic, Equation-solving, Matrices, Vectors, Broadcasting, etc.
• Data Structures and Reading in Pandas, including CSV, Excel, JSON, HTML data
• How to Pre-Process and “Wrangle” your Python data by removing NAs/No data, handling conditional data, grouping by attributes, etc.
• Creating data visualizations like histograms, boxplots, scatterplots, bar plots, pie/line charts, and more!
• Statistical analysis, statistical inference, and the relationships between variables
• Machine Learning, Supervised Learning, Unsupervised Learning in Python
• You’ll even discover how to create artificial neural networks and deep learning structures...& MUCH MORE!
With this course, you’ll have the keys to the entire Python Data Science kingdom!
You’ll start by absorbing the most valuable Python Data Science basics and techniques...
I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in Python.
My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement Python-based data science in real life.
After taking this course, you’ll easily use packages like Numpy, Pandas, and Matplotlib to work with real data in Python.
You’ll even understand deep concepts like statistical modelling in Python’s Statsmodels package and the difference between statistics and machine learning (including hands-on techniques).
I will even introduce you to deep learning and neural networks using the powerful H2o framework!
The underlying motivation for the course is to ensure you can apply Python-based data science on real data and put into practice today. Start analyzing data for your own projects, whatever your skill level and IMPRESS your potential employers with actual examples of your data science abilities.
This course is your one shot way of acquiring the knowledge of statistical data analysis skills that I acquired from the rigorous training received at two of the best universities in the world, a perusal of numerous books and publishing statistically rich papers in renowned international journal like PLOS One.
This course will:
(a) Take students without a prior Python and/or statistics background from a basic level to performing some of the most common advanced data science techniques using the powerful Python-based Jupyter notebooks.
(b) Equip students to use Python for performing different statistical data analysis and visualization tasks for data modelling.
(c) Introduce some of the most important statistical and machine learning concepts to students in a practical manner such that students can apply these concepts for practical data analysis and interpretation.
(d) Students will get a strong background in some of the most important data science techniques.
(e) Students will be able to decide which data science techniques are best suited to answer their research questions and applicable to their data and interpret the results.
It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to data science. However, the majority of the course will focus on implementing different techniques on real data and interpret the results. After each video, you will learn a new concept or technique which you may apply to your own projects.
- Anyone Who Wishes To Learn Practical Data Science Using Python
- Anyone Interested In Learning How To Implement Machine Learning Algorithms Using Python
- People Looking To Get Started In Deep Learning Using Python
- People Looking To Work With Real Life Data In Python
- Anyone With A Prior Knowledge Of Python Looking To Branch Out Into Data Analysis
- Anyone Looking To Become Proficient In Exploratory Data Analysis, Statistical Modelling & Visualizations Using iPython.
Complete Data #Science Training with #Python for #Data Analysis Online #course now 95% discounted check #coupon
https://www.udemy.com/complete-data-science-training-with-python-for-data-analysis/?couponCode=PYTHON_DS10
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