Want to be a data scientist – here are the skills to master

Here are the skills that you will need to master in order to work in the field of data science:
Fundamentals
Programming
Statistics
Advanced machine learning or Deep learning and machine learning
Visualization of Data
Big Data
Data Munging
Data Ingestion
Data-driven problem solving
Toolbox
Fundamentals
Matrices and functions of linear algebra
Binary tree and hash functions
Database basics and relational algebra
Extract Transform Load (ETL)
Reporting VS Business Intelligence (BI) and VS analytics
Statistics
Descriptive Statistics (Variance, Standard Deviation, Range, Median, Mean)
Data Analysis Exploration
Outliers and Percentiles
Theory of Probability
Random Variables
Bayes Theorem
Skewness
Cumulative Distribution function (CDF)
Other statistical fundamentals
Programming
Expert in any one of the programming languages, the recommended ones are R or Python
Advanced Machine Learning (Deep Learning) and Machine Learning
You need to understand what machine learning is and how it works. You should also be able to understand different kinds of techniques of Machine Learning:
Unsupervised learning
Supervised learning
Reinforcement learning
A good level of understanding of the various unsupervised and supervised learning algorithms is needed such as:
Logistic Regression
Linear Regression
Random Forest
Decision Tree
Clustering (for instance K-means)
K Nearest Neighbor
Nowadays a lot of people are talking of Deep Learning, as it has solved a lot of the limitations that used to be encountered when working with the traditional approaches of machine learning. We would recommend that you get at least a basic understanding of how deep learning really works. Here, we list down a few of the concepts of deep learning that you should try to get familiar with:
Any of the libraries that are used for the creation of deep learning models, such as Keras or Tensorflow
Basics of neural networks
Understanding how recurrent neural networks, convolutional neural networks, and Autoencoders and RBM function.
Data Visualization
Data visualization forms a very crucial part of the data life cycle
A very good hands-on skill is needed on different tools used for visualization. You can even use a programming language to achieve this goal. Here are a few of the visualization tools:
Kibana
Tableau
Datawrapper
Google charts
Big Data
Big data seem to be everywhere nowadays and there always seem to be an almost urgent need for collections and preservation of all the data that is being generated, because the tremor of missing out on something that may come back to bite you later is so high.
There is a tremendous amount of the data just floating around. All that matters right now is what we get down to do with it. This is the reason why the analysis of big data is on the frontiers for IT. Analysis of big data has become very crucial since it helps in improving the business, in decision making and in providing the business with an edge over the competition. This applies not only the professionals who work in the domain of Analytics but to companies as well.
So here is a laundry list you may want to keep in mind when you pick a course for yourself.
Resources
So, here we have given you a rundown of the laundry list for you to start working on your skillset if you want to become a data scientist. It may sound scary for you, but it is actually not that hard if you get into a structured program that covers the basics well. We recommend you start with the best Data science course in Mumbai