COMC is hiring for Data Analyst
Salary Range
$80,000.00 - $100,000.00
Apply Link: https://www.paycomonline.net/v4/ats/web.php/jobs/ViewJobDetails?job=100986&clientkey=DB4B2E90705AD5F0635FBD274EAB4268
Job Qualifications
Bachelorโs degree in Computer Science, Information Systems, Statistics, or a related field.
2+ years of experience in data analysis.
Proficient in SQL for data querying and manipulation.
Experience with Power BI or similar data visualization tools.
Understanding of data warehousing and database structures.
Basic knowledge of statistical analysis and data modeling.
Excellent analytical and problem-solving skills.
Ability to communicate complex data insights in a clear and concise manner.
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All the best ๐๐
Salary Range
$80,000.00 - $100,000.00
Apply Link: https://www.paycomonline.net/v4/ats/web.php/jobs/ViewJobDetails?job=100986&clientkey=DB4B2E90705AD5F0635FBD274EAB4268
Job Qualifications
Bachelorโs degree in Computer Science, Information Systems, Statistics, or a related field.
2+ years of experience in data analysis.
Proficient in SQL for data querying and manipulation.
Experience with Power BI or similar data visualization tools.
Understanding of data warehousing and database structures.
Basic knowledge of statistical analysis and data modeling.
Excellent analytical and problem-solving skills.
Ability to communicate complex data insights in a clear and concise manner.
Like for more โค๏ธ
All the best ๐๐
๐5โค1
BCG is hiring for the role of Data Analyst.
Experince - 2 to 4 Years
Location - Bengaluru, Gurgaon
Apply Now : https://unstop.com/o/RYPqncH?lb=8eEx09ow&utm_medium=Share&utm_source=shortUrl
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Experince - 2 to 4 Years
Location - Bengaluru, Gurgaon
Apply Now : https://unstop.com/o/RYPqncH?lb=8eEx09ow&utm_medium=Share&utm_source=shortUrl
Like for more โค๏ธ
All the best ๐๐
Unstop
Data Analyst - Boston Consulting Group - multiple location | 1020224 // Unstop
Become a Data Analyst at Boston Consulting Group and get the best salary in the industry. Click the link to apply now and advance your career. | 2024 | 1020224
โค2๐2
Sharpsell.ai is hiring Business Analyst interns with 0-2 years of experience with a background of Computer Science/Information Systems/ Data Analytics, or a related field.
Candidates with knowledge of SQL and experience writing queries, familiar with BI tools such as Tableau/Power BI, or similar dashboarding platforms are preferred for the role.
This role is for Bangalore location, and three days working from office. Interested candidates please share your CVs with priyadarshini.r@sharpsell.ai
Candidates with knowledge of SQL and experience writing queries, familiar with BI tools such as Tableau/Power BI, or similar dashboarding platforms are preferred for the role.
This role is for Bangalore location, and three days working from office. Interested candidates please share your CVs with priyadarshini.r@sharpsell.ai
๐5
Company: Sanofi!
Position: Trainee Data Analyst
Experienc๏ปฟe: Freshers (0 - 1 Years)
Location: Hyderabad, India
https://sanofi.wd3.myworkdayjobs.com/SanofiCareers/job/Hyderabad/Trainee-Data-Analyst_R2748187
Position: Trainee Data Analyst
Experienc๏ปฟe: Freshers (0 - 1 Years)
Location: Hyderabad, India
https://sanofi.wd3.myworkdayjobs.com/SanofiCareers/job/Hyderabad/Trainee-Data-Analyst_R2748187
๐1
Company: HSBC!
Position: Business Analyst - Accounts
Qualifications: Bachelorโs/ Masterโs Degree
Salary: 7 - 12 LPA (Expected)
Experience: Freshers/ Experienced
Location: Work From Home/ Office
https://mycareer.hsbc.com/en_GB/external/PipelineDetail/Business-Analyst-Accounts-SSI-s/217665
Position: Business Analyst - Accounts
Qualifications: Bachelorโs/ Masterโs Degree
Salary: 7 - 12 LPA (Expected)
Experience: Freshers/ Experienced
Location: Work From Home/ Office
https://mycareer.hsbc.com/en_GB/external/PipelineDetail/Business-Analyst-Accounts-SSI-s/217665
Hsbc
External Careers
๐5
Adobe is hiring!
Position: Data Science Engineer
Qualifications: Bachelorโs/ Masterโs or PhD Degree
Salary: 8 - 23 LPA (Expected)
Experience: Freshers/ Experienced
Location: Bangalore, India
๐Apply Now: https://careers.adobe.com/us/en/job/ADOBUSR144292EXTERNALENUS/Data-Science-Engineer
Position: Data Science Engineer
Qualifications: Bachelorโs/ Masterโs or PhD Degree
Salary: 8 - 23 LPA (Expected)
Experience: Freshers/ Experienced
Location: Bangalore, India
๐Apply Now: https://careers.adobe.com/us/en/job/ADOBUSR144292EXTERNALENUS/Data-Science-Engineer
Amazon is hiring!
Position: Data Analyst/ Business Analytics
Qualifications: Bachelorโs/ Masterโs Degree
Salary: 5 - 8 LPA (Expected)
Experience: Freshers/ Experienced
Location: Bangalore/ Hyderabad
๐Apply Now: https://www.amazon.jobs/en/jobs/2650214/data-analyst-in-easyship?
https://www.amazon.jobs/en/jobs/2574412/business-analyst-i-lat-mile-analytics-and-quality-lmaq?
Position: Data Analyst/ Business Analytics
Qualifications: Bachelorโs/ Masterโs Degree
Salary: 5 - 8 LPA (Expected)
Experience: Freshers/ Experienced
Location: Bangalore/ Hyderabad
๐Apply Now: https://www.amazon.jobs/en/jobs/2650214/data-analyst-in-easyship?
https://www.amazon.jobs/en/jobs/2574412/business-analyst-i-lat-mile-analytics-and-quality-lmaq?
๐1
Gentle reminder ๐๏ธ
"I've seen a great response from you guys and it truly means a lot ๐๐ป ๐ฏ because of your support and efforts, the maximum
number of seats are filled ๐บโ . *I want to inform all of you that the course enrollment will be closed on 20th June 2024 โ ๏ธโ ๏ธ. So, if you're still interested in enrolling in this course please update before 20th June* โบ๏ธโญ
Thank you!!
Regards
Codingdidi
"I've seen a great response from you guys and it truly means a lot ๐๐ป ๐ฏ because of your support and efforts, the maximum
number of seats are filled ๐บโ . *I want to inform all of you that the course enrollment will be closed on 20th June 2024 โ ๏ธโ ๏ธ. So, if you're still interested in enrolling in this course please update before 20th June* โบ๏ธโญ
Thank you!!
Regards
Codingdidi
๐3๐3
Amazon Interview Process for Data Scientist position
๐Round 1- Phone Screen round
This was a preliminary round to check my capability, projects to coding, Stats, ML, etc.
After clearing this round the technical Interview rounds started. There were 5-6 rounds (Multiple rounds in one day).
๐ ๐ฅ๐ผ๐๐ป๐ฑ ๐ฎ- ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐๐ฟ๐ฒ๐ฎ๐ฑ๐๐ต:
In this round the interviewer tested my knowledge on different kinds of topics.
๐๐ฅ๐ผ๐๐ป๐ฑ ๐ฏ- ๐๐ฒ๐ฝ๐๐ต ๐ฅ๐ผ๐๐ป๐ฑ:
In this round the interviewers grilled deeper into 1-2 topics. I was asked questions around:
Standard ML tech, Linear Equation, Techniques, etc.
๐๐ฅ๐ผ๐๐ป๐ฑ ๐ฐ- ๐๐ผ๐ฑ๐ถ๐ป๐ด ๐ฅ๐ผ๐๐ป๐ฑ-
This was a Python coding round, which I cleared successfully.
๐๐ฅ๐ผ๐๐ป๐ฑ ๐ฑ- This was ๐๐ถ๐ฟ๐ถ๐ป๐ด ๐ ๐ฎ๐ป๐ฎ๐ด๐ฒ๐ฟ where my fitment for the team got assessed.
๐๐๐ฎ๐๐ ๐ฅ๐ผ๐๐ป๐ฑ- ๐๐ฎ๐ฟ ๐ฅ๐ฎ๐ถ๐๐ฒ๐ฟ- Very important round, I was asked heavily around Leadership principles & Employee dignity questions.
So, here are my Tips if youโre targeting any Data Science role:
-> Never make up stuff & donโt lie in your Resume.
-> Projects thoroughly study.
-> Practice SQL, DSA, Coding problem on Leetcode/Hackerank.
-> Download data from Kaggle & build EDA (Data manipulation questions are asked)
Resources: https://topmate.io/codingdidi/digital_products
ENJOY LEARNING ๐๐
๐Round 1- Phone Screen round
This was a preliminary round to check my capability, projects to coding, Stats, ML, etc.
After clearing this round the technical Interview rounds started. There were 5-6 rounds (Multiple rounds in one day).
๐ ๐ฅ๐ผ๐๐ป๐ฑ ๐ฎ- ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐๐ฟ๐ฒ๐ฎ๐ฑ๐๐ต:
In this round the interviewer tested my knowledge on different kinds of topics.
๐๐ฅ๐ผ๐๐ป๐ฑ ๐ฏ- ๐๐ฒ๐ฝ๐๐ต ๐ฅ๐ผ๐๐ป๐ฑ:
In this round the interviewers grilled deeper into 1-2 topics. I was asked questions around:
Standard ML tech, Linear Equation, Techniques, etc.
๐๐ฅ๐ผ๐๐ป๐ฑ ๐ฐ- ๐๐ผ๐ฑ๐ถ๐ป๐ด ๐ฅ๐ผ๐๐ป๐ฑ-
This was a Python coding round, which I cleared successfully.
๐๐ฅ๐ผ๐๐ป๐ฑ ๐ฑ- This was ๐๐ถ๐ฟ๐ถ๐ป๐ด ๐ ๐ฎ๐ป๐ฎ๐ด๐ฒ๐ฟ where my fitment for the team got assessed.
๐๐๐ฎ๐๐ ๐ฅ๐ผ๐๐ป๐ฑ- ๐๐ฎ๐ฟ ๐ฅ๐ฎ๐ถ๐๐ฒ๐ฟ- Very important round, I was asked heavily around Leadership principles & Employee dignity questions.
So, here are my Tips if youโre targeting any Data Science role:
-> Never make up stuff & donโt lie in your Resume.
-> Projects thoroughly study.
-> Practice SQL, DSA, Coding problem on Leetcode/Hackerank.
-> Download data from Kaggle & build EDA (Data manipulation questions are asked)
Resources: https://topmate.io/codingdidi/digital_products
ENJOY LEARNING ๐๐
๐10โค2๐ฅ1
Free SQL COURSES!!
https://www.instagram.com/reel/C8jA6lWSYOs/?igsh=MXVwdzdldzBrN204Mw==
1. Introduction to SQL
https://www.simplilearn.com/free-online-course-to-learn-sql-basics-skillup
2.Introduction-to-database-and-sql
https://www.mygreatlearning.com/academy/learn-for-free/courses/introduction-to-database-and-sql
3. My-sql-basics
https://www.mygreatlearning.com/academy/learn-for-free/courses/my-sql-basics
4. Oracle-sql
https://www.mygreatlearning.com/academy/learn-for-free/courses/oracle-sql
5.Advanced-tsql-querying-using-sql-2014
https://www.udemy.com/course/advanced-tsql-querying-using-sql-2014/
6. Sql-for-real-world-data-analysis
https://www.udemy.com/course/sql-for-real-world-data-analysis/
7. advanced-sql( text based)
https://www.kaggle.com/learn/advanced-sql
Share with credit https://t.me/codingdidi
โ โ FOLLOW @CODINGDIDI
https://www.instagram.com/reel/C8jA6lWSYOs/?igsh=MXVwdzdldzBrN204Mw==
Basic- course
1. Introduction to SQL
https://www.simplilearn.com/free-online-course-to-learn-sql-basics-skillup
2.Introduction-to-database-and-sql
https://www.mygreatlearning.com/academy/learn-for-free/courses/introduction-to-database-and-sql
3. My-sql-basics
https://www.mygreatlearning.com/academy/learn-for-free/courses/my-sql-basics
4. Oracle-sql
https://www.mygreatlearning.com/academy/learn-for-free/courses/oracle-sql
Advanced- Course
5.Advanced-tsql-querying-using-sql-2014
https://www.udemy.com/course/advanced-tsql-querying-using-sql-2014/
6. Sql-for-real-world-data-analysis
https://www.udemy.com/course/sql-for-real-world-data-analysis/
7. advanced-sql( text based)
https://www.kaggle.com/learn/advanced-sql
Share with credit https://t.me/codingdidi
โ โ FOLLOW @CODINGDIDI
Simplilearn.com
Free SQL Course Online with Certificate [2025]
Free SQL course online with certificate - master MySQL, PostgreSQL, SQL Server, functions, joins, subqueries and more, and earn a certificate to boost your career.
๐15
๐๐ญ๐ซ๐ข๐ง๐ ๐๐๐ง๐ข๐ฉ๐ฎ๐ฅ๐๐ญ๐ข๐จ๐ง ๐ข๐ง ๐๐ฒ๐ญ๐ก๐จ๐ง:
Strings in Python are immutable sequences of characters.
๐- ๐ฅ๐๐ง(): ๐๐๐ญ๐ฎ๐ซ๐ง๐ฌ ๐ญ๐ก๐ ๐ฅ๐๐ง๐ ๐ญ๐ก ๐จ๐ ๐ญ๐ก๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ .
my_string = "Hello"
length = len(my_string) # length will be 5
๐- ๐ฌ๐ญ๐ซ(): ๐๐จ๐ง๐ฏ๐๐ซ๐ญ๐ฌ ๐ง๐จ๐ง-๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐๐๐ญ๐ ๐ญ๐ฒ๐ฉ๐๐ฌ ๐ข๐ง๐ญ๐จ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฌ.
num = 123
str_num = str(num) # str_num will be "123"
๐- ๐ฅ๐จ๐ฐ๐๐ซ() ๐๐ง๐ ๐ฎ๐ฉ๐ฉ๐๐ซ(): ๐๐จ๐ง๐ฏ๐๐ซ๐ญ ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ญ๐จ ๐ฅ๐จ๐ฐ๐๐ซ๐๐๐ฌ๐ ๐จ๐ซ ๐ฎ๐ฉ๐ฉ๐๐ซ๐๐๐ฌ๐.
my_string = "Hello"
lower_case = my_string.lower() # lower_case will be "hello"
upper_case = my_string.upper() # upper_case will be "HELLO"
๐- ๐ฌ๐ญ๐ซ๐ข๐ฉ(): ๐๐๐ฆ๐จ๐ฏ๐๐ฌ ๐ฅ๐๐๐๐ข๐ง๐ ๐๐ง๐ ๐ญ๐ซ๐๐ข๐ฅ๐ข๐ง๐ ๐ฐ๐ก๐ข๐ญ๐๐ฌ๐ฉ๐๐๐ ๐๐ซ๐จ๐ฆ ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ .
my_string = " Hello "
stripped_string = my_string.strip() # stripped_string will be "Hello"
๐- ๐ฌ๐ฉ๐ฅ๐ข๐ญ(): ๐๐ฉ๐ฅ๐ข๐ญ๐ฌ ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ข๐ง๐ญ๐จ ๐ ๐ฅ๐ข๐ฌ๐ญ ๐จ๐ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฌ ๐๐๐ฌ๐๐ ๐จ๐ง ๐ ๐๐๐ฅ๐ข๐ฆ๐ข๐ญ๐๐ซ.
my_string = "apple,banana,orange"
fruits = my_string.split(",") # fruits will be ["apple", "banana", "orange"]
๐- ๐ฃ๐จ๐ข๐ง(): ๐๐จ๐ข๐ง๐ฌ ๐ญ๐ก๐ ๐๐ฅ๐๐ฆ๐๐ง๐ญ๐ฌ ๐จ๐ ๐ ๐ฅ๐ข๐ฌ๐ญ ๐ข๐ง๐ญ๐จ ๐ ๐ฌ๐ข๐ง๐ ๐ฅ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฎ๐ฌ๐ข๐ง๐ ๐ ๐ฌ๐ฉ๐๐๐ข๐๐ข๐๐ ๐ฌ๐๐ฉ๐๐ซ๐๐ญ๐จ๐ซ.
fruits = ["apple", "banana", "orange"]
my_string = ",".join(fruits) # my_string will be "apple,banana,orange"
๐- ๐๐ข๐ง๐() ๐๐ง๐ ๐ข๐ง๐๐๐ฑ(): ๐๐๐๐ซ๐๐ก ๐๐จ๐ซ ๐ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฐ๐ข๐ญ๐ก๐ข๐ง ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐๐ง๐ ๐ซ๐๐ญ๐ฎ๐ซ๐ง ๐ข๐ญ๐ฌ ๐ข๐ง๐๐๐ฑ.
my_string = "Hello, world!"
index1 = my_string.find("world") # index1 will be 7
index2 = my_string.index("world") # index2 will also be 7
๐- ๐ซ๐๐ฉ๐ฅ๐๐๐(): ๐๐๐ฉ๐ฅ๐๐๐๐ฌ ๐จ๐๐๐ฎ๐ซ๐ซ๐๐ง๐๐๐ฌ ๐จ๐ ๐ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฐ๐ข๐ญ๐ก ๐๐ง๐จ๐ญ๐ก๐๐ซ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ .
my_string = "Hello, world!"
new_string = my_string.replace("world", "Python") # new_string will be "Hello, Python!"
๐- ๐ฌ๐ญ๐๐ซ๐ญ๐ฌ๐ฐ๐ข๐ญ๐ก() ๐๐ง๐ ๐๐ง๐๐ฌ๐ฐ๐ข๐ญ๐ก(): ๐๐ก๐๐๐ค๐ฌ ๐ข๐ ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฌ๐ญ๐๐ซ๐ญ๐ฌ ๐จ๐ซ ๐๐ง๐๐ฌ ๐ฐ๐ข๐ญ๐ก ๐ ๐ฌ๐ฉ๐๐๐ข๐๐ข๐๐ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ .
my_string = "Hello, world!"
starts_with_hello = my_string.startswith("Hello") # True
ends_with_world = my_string.endswith("world") # False
๐๐- ๐๐จ๐ฎ๐ง๐ญ(): ๐๐จ๐ฎ๐ง๐ญ๐ฌ ๐ญ๐ก๐ ๐จ๐๐๐ฎ๐ซ๐ซ๐๐ง๐๐๐ฌ ๐จ๐ ๐ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ข๐ง ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ .
my_string = "apple, banana, orange, banana"
count = my_string.count("banana") # count will be 2
Python pandas Complete
๐๐
https://topmate.io/codingdidi
Hope you'll like it
Like this post if you need more resources like this ๐โค๏ธ
Strings in Python are immutable sequences of characters.
๐- ๐ฅ๐๐ง(): ๐๐๐ญ๐ฎ๐ซ๐ง๐ฌ ๐ญ๐ก๐ ๐ฅ๐๐ง๐ ๐ญ๐ก ๐จ๐ ๐ญ๐ก๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ .
my_string = "Hello"
length = len(my_string) # length will be 5
๐- ๐ฌ๐ญ๐ซ(): ๐๐จ๐ง๐ฏ๐๐ซ๐ญ๐ฌ ๐ง๐จ๐ง-๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐๐๐ญ๐ ๐ญ๐ฒ๐ฉ๐๐ฌ ๐ข๐ง๐ญ๐จ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฌ.
num = 123
str_num = str(num) # str_num will be "123"
๐- ๐ฅ๐จ๐ฐ๐๐ซ() ๐๐ง๐ ๐ฎ๐ฉ๐ฉ๐๐ซ(): ๐๐จ๐ง๐ฏ๐๐ซ๐ญ ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ญ๐จ ๐ฅ๐จ๐ฐ๐๐ซ๐๐๐ฌ๐ ๐จ๐ซ ๐ฎ๐ฉ๐ฉ๐๐ซ๐๐๐ฌ๐.
my_string = "Hello"
lower_case = my_string.lower() # lower_case will be "hello"
upper_case = my_string.upper() # upper_case will be "HELLO"
๐- ๐ฌ๐ญ๐ซ๐ข๐ฉ(): ๐๐๐ฆ๐จ๐ฏ๐๐ฌ ๐ฅ๐๐๐๐ข๐ง๐ ๐๐ง๐ ๐ญ๐ซ๐๐ข๐ฅ๐ข๐ง๐ ๐ฐ๐ก๐ข๐ญ๐๐ฌ๐ฉ๐๐๐ ๐๐ซ๐จ๐ฆ ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ .
my_string = " Hello "
stripped_string = my_string.strip() # stripped_string will be "Hello"
๐- ๐ฌ๐ฉ๐ฅ๐ข๐ญ(): ๐๐ฉ๐ฅ๐ข๐ญ๐ฌ ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ข๐ง๐ญ๐จ ๐ ๐ฅ๐ข๐ฌ๐ญ ๐จ๐ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฌ ๐๐๐ฌ๐๐ ๐จ๐ง ๐ ๐๐๐ฅ๐ข๐ฆ๐ข๐ญ๐๐ซ.
my_string = "apple,banana,orange"
fruits = my_string.split(",") # fruits will be ["apple", "banana", "orange"]
๐- ๐ฃ๐จ๐ข๐ง(): ๐๐จ๐ข๐ง๐ฌ ๐ญ๐ก๐ ๐๐ฅ๐๐ฆ๐๐ง๐ญ๐ฌ ๐จ๐ ๐ ๐ฅ๐ข๐ฌ๐ญ ๐ข๐ง๐ญ๐จ ๐ ๐ฌ๐ข๐ง๐ ๐ฅ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฎ๐ฌ๐ข๐ง๐ ๐ ๐ฌ๐ฉ๐๐๐ข๐๐ข๐๐ ๐ฌ๐๐ฉ๐๐ซ๐๐ญ๐จ๐ซ.
fruits = ["apple", "banana", "orange"]
my_string = ",".join(fruits) # my_string will be "apple,banana,orange"
๐- ๐๐ข๐ง๐() ๐๐ง๐ ๐ข๐ง๐๐๐ฑ(): ๐๐๐๐ซ๐๐ก ๐๐จ๐ซ ๐ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฐ๐ข๐ญ๐ก๐ข๐ง ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐๐ง๐ ๐ซ๐๐ญ๐ฎ๐ซ๐ง ๐ข๐ญ๐ฌ ๐ข๐ง๐๐๐ฑ.
my_string = "Hello, world!"
index1 = my_string.find("world") # index1 will be 7
index2 = my_string.index("world") # index2 will also be 7
๐- ๐ซ๐๐ฉ๐ฅ๐๐๐(): ๐๐๐ฉ๐ฅ๐๐๐๐ฌ ๐จ๐๐๐ฎ๐ซ๐ซ๐๐ง๐๐๐ฌ ๐จ๐ ๐ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฐ๐ข๐ญ๐ก ๐๐ง๐จ๐ญ๐ก๐๐ซ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ .
my_string = "Hello, world!"
new_string = my_string.replace("world", "Python") # new_string will be "Hello, Python!"
๐- ๐ฌ๐ญ๐๐ซ๐ญ๐ฌ๐ฐ๐ข๐ญ๐ก() ๐๐ง๐ ๐๐ง๐๐ฌ๐ฐ๐ข๐ญ๐ก(): ๐๐ก๐๐๐ค๐ฌ ๐ข๐ ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ฌ๐ญ๐๐ซ๐ญ๐ฌ ๐จ๐ซ ๐๐ง๐๐ฌ ๐ฐ๐ข๐ญ๐ก ๐ ๐ฌ๐ฉ๐๐๐ข๐๐ข๐๐ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ .
my_string = "Hello, world!"
starts_with_hello = my_string.startswith("Hello") # True
ends_with_world = my_string.endswith("world") # False
๐๐- ๐๐จ๐ฎ๐ง๐ญ(): ๐๐จ๐ฎ๐ง๐ญ๐ฌ ๐ญ๐ก๐ ๐จ๐๐๐ฎ๐ซ๐ซ๐๐ง๐๐๐ฌ ๐จ๐ ๐ ๐ฌ๐ฎ๐๐ฌ๐ญ๐ซ๐ข๐ง๐ ๐ข๐ง ๐ ๐ฌ๐ญ๐ซ๐ข๐ง๐ .
my_string = "apple, banana, orange, banana"
count = my_string.count("banana") # count will be 2
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Expand your job search to increase your chances of becoming a data analyst.
Here are alternative roles to explore:
1. ๐๐๐๐ถ๐ป๐ฒ๐๐ ๐๐ป๐ฎ๐น๐๐๐: Focuses on using data to improve business processes and decision-making.
2. ๐ข๐ฝ๐ฒ๐ฟ๐ฎ๐๐ถ๐ผ๐ป๐ ๐๐ป๐ฎ๐น๐๐๐: Specializes in analyzing operational data to optimize efficiency and performance.
3. ๐ ๐ฎ๐ฟ๐ธ๐ฒ๐๐ถ๐ป๐ด ๐๐ป๐ฎ๐น๐๐๐: Uses data to drive marketing strategies and measure campaign effectiveness.
4. ๐๐ถ๐ป๐ฎ๐ป๐ฐ๐ถ๐ฎ๐น ๐๐ป๐ฎ๐น๐๐๐: Analyzes financial data to support investment decisions and financial planning.
5. ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐ ๐๐ป๐ฎ๐น๐๐๐: Evaluates product performance and user data to help product development.
6. ๐ฅ๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐๐ป๐ฎ๐น๐๐๐: Conducts data-driven research to support strategic decisions and policy development.
7. ๐๐ ๐๐ป๐ฎ๐น๐๐๐: Transforms data into actionable business insights through reporting and visualization.
8. ๐ค๐๐ฎ๐ป๐๐ถ๐๐ฎ๐๐ถ๐๐ฒ ๐๐ป๐ฎ๐น๐๐๐: Utilizes statistical and mathematical models to analyze large datasets, often in finance.
9. ๐๐๐๐๐ผ๐บ๐ฒ๐ฟ ๐๐ป๐๐ถ๐ด๐ต๐๐ ๐๐ป๐ฎ๐น๐๐๐: Analyzes customer data to improve customer experience and drive retention.
10. ๐๐ฎ๐๐ฎ ๐๐ผ๐ป๐๐๐น๐๐ฎ๐ป๐: Provides expert advice on data strategies, data management, and analytics to organizations.
11. ๐ฆ๐๐ฝ๐ฝ๐น๐ ๐๐ต๐ฎ๐ถ๐ป ๐๐ป๐ฎ๐น๐๐๐: Analyzes supply chain data to optimize logistics, reduce costs, and improve efficiency.
12. ๐๐ฅ ๐๐ป๐ฎ๐น๐๐๐: Uses data to improve human resources processes, from recruitment to employee retention and performance management.
Hope this helps you ๐
Here are alternative roles to explore:
1. ๐๐๐๐ถ๐ป๐ฒ๐๐ ๐๐ป๐ฎ๐น๐๐๐: Focuses on using data to improve business processes and decision-making.
2. ๐ข๐ฝ๐ฒ๐ฟ๐ฎ๐๐ถ๐ผ๐ป๐ ๐๐ป๐ฎ๐น๐๐๐: Specializes in analyzing operational data to optimize efficiency and performance.
3. ๐ ๐ฎ๐ฟ๐ธ๐ฒ๐๐ถ๐ป๐ด ๐๐ป๐ฎ๐น๐๐๐: Uses data to drive marketing strategies and measure campaign effectiveness.
4. ๐๐ถ๐ป๐ฎ๐ป๐ฐ๐ถ๐ฎ๐น ๐๐ป๐ฎ๐น๐๐๐: Analyzes financial data to support investment decisions and financial planning.
5. ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐ ๐๐ป๐ฎ๐น๐๐๐: Evaluates product performance and user data to help product development.
6. ๐ฅ๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐๐ป๐ฎ๐น๐๐๐: Conducts data-driven research to support strategic decisions and policy development.
7. ๐๐ ๐๐ป๐ฎ๐น๐๐๐: Transforms data into actionable business insights through reporting and visualization.
8. ๐ค๐๐ฎ๐ป๐๐ถ๐๐ฎ๐๐ถ๐๐ฒ ๐๐ป๐ฎ๐น๐๐๐: Utilizes statistical and mathematical models to analyze large datasets, often in finance.
9. ๐๐๐๐๐ผ๐บ๐ฒ๐ฟ ๐๐ป๐๐ถ๐ด๐ต๐๐ ๐๐ป๐ฎ๐น๐๐๐: Analyzes customer data to improve customer experience and drive retention.
10. ๐๐ฎ๐๐ฎ ๐๐ผ๐ป๐๐๐น๐๐ฎ๐ป๐: Provides expert advice on data strategies, data management, and analytics to organizations.
11. ๐ฆ๐๐ฝ๐ฝ๐น๐ ๐๐ต๐ฎ๐ถ๐ป ๐๐ป๐ฎ๐น๐๐๐: Analyzes supply chain data to optimize logistics, reduce costs, and improve efficiency.
12. ๐๐ฅ ๐๐ป๐ฎ๐น๐๐๐: Uses data to improve human resources processes, from recruitment to employee retention and performance management.
Hope this helps you ๐
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I want to inform you that the MySQL classes ๐ฉ๐ปโ๐ซ will be starting from 10th July ๐๏ธ if you're interested please enroll in the classes ASAP ๐ as there are limited seats ๐บ.
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Hi [Name],
I hope this message finds you well.
My name is [Your Name], and I recently graduated with a degree in [Your Degree] from [Your University]. I am passionate about data analytics and have developed a strong foundation through my coursework and practical projects.
I am currently seeking opportunities to start my career as a Data Analyst and came across the exciting roles at [Company Name].
I am reaching out to you because I admire your professional journey and expertise in the field of data analytics. Your role at [Company Name] is particularly inspiring, and I am very interested in contributing to such an innovative and dynamic team.
I am confident that my skills and enthusiasm would make me a valuable addition to this role [Job ID / Link]. If possible, I would be incredibly grateful for your referral or any advice you could offer on how to best position myself for this opportunity.
Thank you very much for considering my request. I understand how busy you must be and truly appreciate any assistance you can provide.
Best regards,
[Your Full Name]
[Your Email Address]
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Hi [Name],
I hope this message finds you well.
My name is [Your Name], and I recently graduated with a degree in [Your Degree] from [Your University]. I am passionate about data analytics and have developed a strong foundation through my coursework and practical projects.
I am currently seeking opportunities to start my career as a Data Analyst and came across the exciting roles at [Company Name].
I am reaching out to you because I admire your professional journey and expertise in the field of data analytics. Your role at [Company Name] is particularly inspiring, and I am very interested in contributing to such an innovative and dynamic team.
I am confident that my skills and enthusiasm would make me a valuable addition to this role [Job ID / Link]. If possible, I would be incredibly grateful for your referral or any advice you could offer on how to best position myself for this opportunity.
Thank you very much for considering my request. I understand how busy you must be and truly appreciate any assistance you can provide.
Best regards,
[Your Full Name]
[Your Email Address]
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What roles make it easier to get into Data Science?
Most of Data Scientists usually transitioned in from other roles
The most common ones, are - Data Analyst, Business Intelligence Engineer and Data Engineer.
For a fresher with only a bachelors degree, I would advise the Data Analyst role. Based on the team and work, you may in essence be able to work as a Data Scientist.
Most of Data Scientists usually transitioned in from other roles
The most common ones, are - Data Analyst, Business Intelligence Engineer and Data Engineer.
For a fresher with only a bachelors degree, I would advise the Data Analyst role. Based on the team and work, you may in essence be able to work as a Data Scientist.
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