I am in my 4th year of bachelors and i don't have any technical skills but I'm interested to learn skills which are related to become a data scientist or analyst and I'm interested to take up jobs related to business analyst but i dont know where to start and what to study and how to apply .i need help. Can anyone guide me what to study and how to apply and give me a schedule of how many hours I should study to improve my skills
Browse recent posts
A few comments on the terrible job market and how overly critical the hiring side is on this right now:
If the job market changes a lot of companies and some recruiters (probably more on the company side since a lot of recruiters are good at what they do and don't get enough credit) are going to be in big trouble because the people getting the jobs now will be leaving as soon as it…
0 Likes • 2 Comments
Get Ready: Inspo Summit Is Back and Bigger Than Ever
The countdown is ON for our fifth-annual Inspiration Summit, the signature event of the year for the Fairygodboss and The Muse communities.
Expect powerhouse sessions like:
A Game-Changing Approach to Modern…
0 Likes • 0 Comments
Hello Fairies,
So I applied for a job this year and I recently got this in my email : “We regret to inform you that, following a thorough review of the background check results, we are unable to proceed with your offer of employment at this time. The decision was made based on information uncovered…
1 Like • 20 Comments
? Truth: No force is more powerful than someone on the job hunt.
Nothing stands in your way when you're focused, fueled by purpose, and ready to take control of your next chapter. ?
Whether you're re-entering the workforce, pivoting industries, or just ready for more... this season is YOURS.…
2 Likes • 0 Comments
I sent my draft resume to a job posting by accident
I submitted the resume again with the correct resume should I email them and let them know ? Guess I should kiss this role bye bye lol after this mistake !
0 Likes • 2 Comments
Dealing with call outs
I’m curious if others experience noisy co workers even management asking why you called out. And what do you say? I’m personally starting to find it annoying. Does anyone else find it annoying and what do you say?
1 Like • 12 Comments
Share your insight
Join an authentic community that helps women support each other at work. Share your professional experience or ask for advice — you can even post anonymously.
Mary Wehrle
Use this website. I put in data analyst for the search. There is a list of possible positions. Each one with a sun, has a positive outlook for a growing industry.
If you look into each position, there will be a general description of duties and required education and experience. This will help target you education. Hope this helps
https://www.onetonline.org/find/result?s=Data+analyst+
Anonymous
Thanks a lotttt!
Comment deleted by user
Abkhen Berg
Learning data science involves acquiring a mix of skills in programming, statistics, and domain knowledge, along with hands-on experience with data.
Start by brushing up on the foundational math and stats concepts, including probability, distributions, hypothesis testing, linear algebra, and calculus. These are essential for understanding data science algorithms.
Learn SQL and programming in Python and the many libraries available. R can also be useful.
Learn how to handle missing data, remove duplicates, and transform raw data into a usable format.
Learn how to visualize data to find insights. Besides Matplotlib and Seaborn, you might also want to learn about tools like Tableau or Power BI if you want to be an analyst.
Learn about different data analysis techniques: descriptive, diagnostic, predictive, and prescriptive analytics. Understand how to explore data, find patterns, and generate insights using exploratory data analysis (EDA).
Learn Machine learning: Supervised Learning: Understand algorithms like linear regression, logistic regression, decision trees, and support vector machines.
Unsupervised Learning: Learn about clustering (like K-means) and dimensionality reduction techniques (like PCA).
Deep Learning: If you're interested, learn about neural networks using libraries like TensorFlow or PyTorch.
Use publicly available datasets from sources like Kaggle, UCI Machine Learning Repository, or government data portals. Participate in Kaggle competitions to test your skills against other data scientists.
Understand Data Science Tools and Frameworks like Jupyter Notebook, Git for version control, and cloud platforms like AWS or Google Cloud for deploying models. Frameworks for machine learning such as TensorFlow, Keras, or PyTorch.
Start with simple projects and gradually increase complexity. For example, start with data cleaning and visualization projects, move to predictive modeling, and then complex machine learning projects. Document your projects and maintain a portfolio, which can be helpful for job applications.
Follow data science blogs, podcasts, and forums like Towards Data Science, KDnuggets, or Reddit's r/datascience. Attend meetups, webinars, or conferences to network with other data science professionals.
Consider online courses and certifications from platforms like Coursera, edX, Udacity, DataCamp and/or DataQuest.
Be patient and consistent, you'll gradually build the knowledge and skills required to become proficient in data science. Hands-on practice and real-world application are key, so focus on doing as much as learning. Learning data science involves acquiring a mix of skills in programming, statistics, and domain knowledge, along with hands-on experience with data.
There are no accredited certifications, and it would help if you get a Masters in DS or Analytics. I love going to work every day, it is an interesting and knowledge filled profession. Good luck.
Anonymous