Learn (DA/DS ) To Earn $40-$200 Per hour
Earn Monthly $20000
Per Hours Training fee $ 20
Payment On Condition Installment: 50% Advance ,50 % after income
Total training hours for Data Analytics 1500-1600 as per trainee capacity
Total Practice Time 4500-5400 hours
Weekly 6/18/36/72 hours, Monthly 8 hours to 100 hours ,Total 5 Years to 1 Year
Traininig Time 1 hour : Practice Time 3 hours
FOR DATA SCIENCE 4 LEVELS 30 STEPS
Learn (DA/DS ) To Earn $40-$200 Per hour
Earn Monthly $20000
Per Hours Training fee $ 20
Payment On Condition Installment: 50% Advance ,50 % after income
Total training hours for Data Analytics 500-600 as per trainee capacity
Total Practice Time 1500-1800 hours
Weekly 2/6/12/20 hours ,Monthly 8 hours to 80 hours ,
Total 5 Years ( for Students / Part time learner ) to 6 Months (for Professionals)
Traininig Time 1 hour : Practice Time 3 hours
FOR DATA SCIENCE 4 LEVELS 30 STEPS
1.Beginners Level
Step 1. Practical Learning :Tools 1.Excel 2.Power BI 3.SQL 4. Python for DS 5.Extra ML for DS
Step 2.Application of learning/Projects Baised Learning:Duplicate Projects i). Individual projects 2) Combined projects
2.Intermediate Level :Internship
Step-3. Internal Internship . i.clipchamp :video editing ii.Audio recording iii.Screen recording iv.YouTube upload procedure v.Graphics for thumbnail vi.Linked in banner vii.Profile Picture viii.Canva ix. Chat GPT x. AI and others
Step-4.International Internship -GRIP & from others
Steep-5.Certification : Microsoft,Google & others Certification: Theoretical and Practical for Data Analytics PL-300, /individuals Excel/Power BI/SQL/Python
World Queen University (Professional)
Step-6.Resume & CV
Step-7. IELTS/English listening,Speaking ,Reading ,Writing skills
.i.Interview Preparation
ii. Client Dealing
iii. Email Reading & Writing
3.Advanced Level for Professional :
Step-8. Work Exam->Upwork Language Test Enlish Fluency ->->Upwork Readiness Test-> Upwork DA/DS Test
Step-9.Join Agency/Group
Step-10-i.Portfolios Projects to Github ,Novyo,Datascience.com ii.Linkedin iii. My Credible info and others account
Step11.Live Data Projects by won 20
Step-12.International Paid Internship
Step-13.Up work Problem solve
Step-14.Earn :Freelance :UP WORK
Step 15.Earn :Remote Job
Summary of DS
[1] Data Science is not just about building a dashboard in 15 minutes or 1 hour. It is a minor part of data analyst work.
[2] It is not that easy for freshers or anyone to get a DA job as it is glorified on the internet. As of Aug 2024 there is a huge competition and limited roles. A fresher should do something outstanding to get recruiters attention- like having a solid project portfolio, online credibility on LinkedIn, cold emailing, messaging on LinkedIn to get recommendations etc.
[3] Do not buy any paid course directly if you have no idea about this field. Spend 3-4 days on solid research. Learn from free resources first to understand if you like this role, do more research about market conditions. Most importantly do not blindly believe anyone on the internet – do your own research.
[4] Offline networking can be a game changer for both freshers, people with career break and experienced people from wanting to transition career. Check for the offline events near your place and join them.
[5] 100 % Job guarantee, pay after placement, get 24 LPA – all these are scams running in the market. If you do not pay time extra for research you will loose both your money and time.
[6] Domain knowledge is key. Freshers can domain knowledge by starting with business KPIs, understanding the business process behind the apps use, checking customer stories on Microsoft, following case studies, solving unguided projects (check codebasics resume project challenges – https://codebasics.io/challenge/codebasics-resume-project-challenge). This won’t completely replace the need for practical experience but it will be better than having no experience.
[7] People with career gap or transitioning career should try to combine their past domain experience with their tool skills to make a strong resume and apply for roles particular to that domain. For example, a person with sales experience in telecom domain should have projects particular to that domain/function to show relevant experience and also maintain the salary range.
Level-4.Move to Data Science
Step-15 Machine Learning
Step-16.Deep Learning
Step-18.Mathematics for Data Science
Step-19.Statistics for Data Science
Step-20.R for Data Science
Step-21.Web scraping
Step-22.Predictive Modelling
Step-23.NLP
Step-24.Java for Data Science
Step -25.Certification of Data Science from Microsoft/IBM
Step-26.Project of Data Science 20
Step-27.Prediction Projects of DS
Step-28.Update CV,Resume and Others Accounts
Step-29.Certification of Data Science
Step-30.Apply Data Science Job and Earn Monthly $20000
FOR DATA SCIENCE
Total Training Time 1200 -1500 hours as per trainee capacity
Total Practice Time 3600-4500 hours
Minimum 12 Tools
Demand: With the rise of AI, the role of data scientist might change and evolve as the role stays in high demand. Among career websites such as Glassdoor, data scientist job titles consistently rank as “top jobs” based on criteria such as salary, job market prognosis and job satisfaction. Data scientist is a new position that has grown because of the increasing use of big data. The number of data scientist jobs is projected to rise 35% between 2022 and 2032. This equates to the creation of 59,400 new jobs, according to data from the BLS.
