[00:01] there are several essential skills you need to master let's type in and check need to master let's type in and check them out one by analyzing data to help make Better Business decisions you'll need to get
[00:16] good at various skills from math and programming to data handling and visualization let's jump in first up you need a solid foundation in mathematics and statistics this is crucial because data analysis relies heavily on these
[00:29] principles focus on understanding basic concepts like mean median standard deviation probability and hypothesis testing spend about a month or two getting comfortable with these topics next you need to get really good at
[00:43] Excel Excel is a powerful tool for data analysis and many companies still rely on it learn how to use functions pivot tables and charts spend about 2 to 3 weeks mastering Excel as it's a fundamental skill for any data analyst
[00:58] after Excel you should get comfortable with SQL SQL stands for structured query language it's a simple language we use for managing and querying databases learn how to write queries to access organize and analyze data SQL is pretty
[01:13] simple and you can get a decent grasp of it in about a month or two next you need to get the hang of python it's a versatile language that's widely used in data analysis focus on learning the basics of python including libraries
[01:27] like pandas and nonp you will also hear about r R that's another language used in data analysis however if you're starting out it's best to stick with python first and think about learning R later spend about a month or two getting
[01:40] the hang of python you should also learn git that's a Version Control System we use to track changes to our code and collaborate with others git has a ton of features but you don't need to learn all of them think of it like the 8020 rule
[01:52] 80% of the time you use 20% of GS features so one to two weeks of practice way to help you on this journey I've created a free supplementary PDF that
[02:04] breaks down the specific Concepts you need to learn for each skill it's a great resource to review your progress find gaps in your knowledge and prepare for interviews you can find the link in the description also I have a bunch of
[02:16] tutorials on this channel and complete courses on my website if you're looking for structured learning again links are in the description next focus on data collection and preparation this means Gathering data from various sources and
[02:29] analysis learn how to use Python libraries like pandas to manipulate and clean data spend about a month or two on this once your data is clean you need to visualize it to spot patterns and communicate results learn how to use
[02:44] Python libraries like ma plot lib and Seaborn also check out business intelligence tools like Tableau or powerbi they are widely used for creating interactive and sharable dashboards powerbi is especially cool
[02:56] because it's getting more popular and since it's a Microsoft product it works might be using spend about a month or two on data visualization now while not essential for every data analyst role having a basic understanding of machine
[03:11] learning can be a plus machine learning involves teaching computers to make predictions Based on data if you're interested spend a month or two learning the basics of machine learning including python libraries like tensor flow and
[03:24] psychic learn now as you advance you might encounter situations where you need to work with Ma massive data sets that's where Big Data comes in Big Data is all about handling and processing huge amounts of data quickly tools like
[03:38] Hadoop and Spark are super handy for this spend a month or two getting familiar with these tools so if you dedicate 3 to 5 hours every day you can follow this road map and pick up all the skills you need to apply for an
[03:51] entry-level data analyst job in about 8 to 16 months if you have any questions and I'll do my best to answer you right enjoyed this video please give it a like And subscribe for more useful content
[04:05] And subscribe for more useful content thanks for watching