How to Become Data Scientist - Best Online Data Science Courses & Books

How to Become Data Scientist - Best Online Data Science Courses & Books

If you’re a job seeker and becoming a data scientist is your dream?

But you don’t know what to study and how to achieve your goal and What are the best online data science courses to get in to this lucarative career?

Then you came to the right place.

In this article you can find

1. Who is a data scientist?

2. What does a data scientist do?

3. How to become a data scientist?

4. Best Online Data science Courses to become a data scientist

5. Best Data Scientist Books.

how to become a Data Scientist

Let’s start.

Who is a data scientist?

Data Scientist performs data analysis on data stored in data warehouses or data centers to solve a variety of business problems, optimize performance and gather business intelligence.

Let me explain Consider Amazon, India’s largest online shopping store. It gets 2.15B visits per day.

Each visitor visits at least 10 pages for session.

So these user activities produce a huge amount of data.

It may be related to inventory, sales, marketing, transactional and other business related activities. Amazon maintains all these data in their data servers. If Amazon wants to know

Which pages are getting more visits?

Which items are selling quickly?

What are the characteristics of the users?

This is where a data scientist takes his role.

To get answers to all these questions, the data scientist collects and presents the data in a required format.

There are a lot of trends or patterns in the stored data which need to be mined so that business can use it for future.

To find all these patterns, the data scientist should investigate the data. If these relationships or patterns can be recognized and made insightful, then it helps business in different ways.

2. What does a data scientist do?

What does a data scientist do?

The next question came to your mind.

Is it right or not?

The main function of data scientist is "depending on the present data, he should produce detailed predictions of what the future will hold".

Here is the list of activities what a data scientist actually does day-to-day.

These steps remain more or less the same for any data scientist to work through a complex business problem.

1. Frame the problem

2. Collect the raw data needed to solve the problem

3. Process the data (data wrangling)

4. Explore the data

5. Perform in-depth analysis (machine learning, statistical models, algorithms)

6. Communicate results of the analysis

3. How to become a data scientist?

Day by day demand for the data scientist jobs is increasing. IBM Predicts Demand For Data Scientists Will Soar 28% By 2020.

Data Scientist Qualifications

To become a data scientist you must have a university degree in any field like Science, Technology, Engineering or Math or equivalent professional experience and you must

Learn Programming skills in R, Scala and Python

Have knowledge of visualization tools such as Tableau, Microsoft Power BI

Hadoop and Apache Spark

Learn the fundamentals of machine learning algorithms

Learn the important tools of the trade – SPSS, Apache Spark, SQL

Data Scientist Salary

A Data Scientist, IT earns an average salary of Rs 620,244 per year. Experience strongly influences income for this job.

The highest paying skills associated with this job are Data Mining / Data Warehouse, Machine Learning, Java, Apache Hadoop, and Python.

4. Best Online Data science Courses to become a data scientist

To become a data scientist, find the right course and increase your analytical skills if you don't have knowledge. It helps you to boost Your Career Growth.

Here is the list of best online data science courses to become a data scientist.

1. Coursera- Data Science Specialization

This Data Science specialization course is created by John Hopkins University.

This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results.

Curricular for Coursera - Data Science Specialization

1. The Data Scientist’s Toolbox

2. R Programming

3. Getting and Cleaning Data

4. Exploratory Data Analysis

5. Reproducible Research

6. Statistical Inference

7. Regression Models

8. Practical Machine Learning

9. Developing Data Products

10. Data Science Capstone

2. Coursera – Data-Driven Decision Making

Coursera Data-driven Decision Making is created by PricewaterhouseCoopers LLP.

In this course you'll get an introduction to Data Analytics and its role in business decisions.

In this four-week course you can learn how business organizations are using data analytics to solve their problems.

Different modules of Coursera – Data-Driven Decision Making

1. Introduction to Data Analytics

2. Technology and types of data

3. Data analysis techniques and tools

4. Data-driven decision making project

3. Data Science A-Z: Real-Life Data Science Exercises Included

If you are ready to enter into this lucrative career, then learn the real problems of data scientist.

This course is created by Data Science management consultant Kirill Eremenko.

In this course you can learn Data Science step by step through real Analytics examples.

It is a best-selling data scientist courses. In which more than 46K students are enrolled.

Curriculum For Data Science A-Z: Real-Life Data Science Exercises Included Course

1. What is Data Science?

2. Visualisation

3. Data Preparation

4. Communication

4. Machine Learning A-Z™: Hands-On Python & R In Data Science

Do you have interest in machine learning.

Then this course is suitable for you.

This course created by two professional Data Scientists Created by Kirill Eremenko & Hadelin de Ponteves.

This course is packed with practical exercises which are based on live examples.

It is a best-selling course in Data Science. In which more than 92K students are enrolled.

In this course you can learn to create Machine Learning Algorithms in Python and R.

Curricular for Machine Learning A-Z™: Hands-On Python & R In Data Science

Part 1 - Data Preprocessing

Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression

Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification

Part 4 - Clustering: K-Means, Hierarchical Clustering

Part 5 - Association Rule Learning: Apriori, Eclat

Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling

Part 7 - Natural Language Processing: Bag-of-words model and algorithms for NLP

Part 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural Networks

Part 9 - Dimensionality Reduction: PCA, LDA, Kernel PCA

Part 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost

5. R Programming A-Z: R For Data Science With Real Exercises

If you want to learn how to program in R, then this course is suitable for you.

It is 10.5 hours on-demand video course.

This course is suitable for all levels of students. Even if you don’t have any programming and statistical background.

Curriculum For R Programming A-Z: R For Data Science With Real Exercises

1. The Ground Running

2. Core Programming Principles

3. Fundamentals Of R

4. Matrices

5. Data Frames

6. Advanced Visualization With GGPlot2

6. Statistics for Business Analytics A-Z

If you want to become a data scientist, then you must have knowledge of basic statistics.

In this course, you can learn the absolutely essential stats knowledge for a Data Scientist or Analyst through real world examples.

This course is created by Created by Kirill Eremenko and around 4K students are enrolled in this course. This course contains 7 hours on demand course.

Curriculum For Statistics for Business Analytics A-Z

1. Distributions

2. Central Limit Theorem

3. Hypothesis Testing / Statistical Significance

4. Advanced Hypothesis Testing

5. Vitaly Dolgov's Guest Section

7. Tableau 10 A-Z: Hands-On Tableau Training For Data Science

In this course you can Learn data visualization through Tableau 10.

Tableau allows you to explore, experiment with, fix, prepare, and present data easily, quickly, and beautifully.

This course has been created by Kirill Eremenko and around 17K students are enrolled in this best selling course.

Curriculum of Tableau 10 A-Z: Hands-On Tableau Training For Data Science

1. Get Started

2. Tableau Basics: Your First Bar chart

3. Time series, Aggregation, and Filters

4. Maps, Scatterplots, and Your First Dashboard

5. Joining and Blending Data, PLUS: Dual Axis Charts

6. Table Calculations, Advanced Dashboards, Storytelling

7. Advanced Data Preparation

8. What's new in Tableau 10

8. SQL & Database Design A-Z: Learn MS SQL Server + PostgreSQL

If you want to lear PostgreSQL, which is a popular variation of SQL.

Then this course is suitable for you. This best selling course is created by Kirill Eremenko who is Data Scientist & Forex Systems Expert and Ilya Eremenko who is Business Analyst Professional.

Curriculum of SQL & Database Design A-Z: Learn MS SQL Server + PostgreSQL

1. Introduction

2. Installation

3. Preparation

4. Basics of SQL

5. Working With Data

6. Fundamentals of Database Theory

7. Joining tables in SQL

8. Creating Tables in SQL

9. Database Design

9. The Ultimate Hands-On Hadoop - Tame your Big Data

This course is suitable for Software engineers and programmers who want to understand the larger Hadoop ecosystem, and use it to store, analyze, and vend "big data" at scale.

With this course you can understand Hadoop and its associated distributed systems, and apply Hadoop to real-world problems.

This course is comprehensive, covering over 25 different technologies in over 14 hours of video lectures.

Curriculum of The Ultimate Hands-On Hadoop - Tame your Big Data

1. Learn all the buzzwords! And install Hadoop.

2. Using Hadoop's Core: HDFS and MapReduce

3. Programming Hadoop with Pig

4. Programming Hadoop with Spark

5. Using relational data stores with Hadoop

6. Using non-relational data stores with Hadoop

7. Querying Your Data Interactively

8. Managing your Cluster

9. Feeding Data to your Cluster

10. Analyzing Streams of Data

11. Designing Real-World Systems

5. Best Data Scientist Books

There are lots of books available to study about data science and to learn R and Python languages. Here is the list of the books which are suitable for people who want to learn programming and statistics which are core skills to become a data scientist.

1. R Cookbook by Paul Teetor

2. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

3. Hands-on Programming with R by Grolemund (Author), Garrett (Author)

4. R graphics cookbook by Winston Chang

5. R for Everyone: Advanced Analytics and Graphics

6. Machine Learning with R by Brett Lantz

7. Mastering Machine Learning with R by Cory Lesmeister

8. Practical Data Science with R by Nina Zumel and John Mount

9. Mastering Python for Data Science by Samir Madhavan

10. Python for Data Analysis

11. Python Machine Learning

12. An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics) by Gareth James