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Changing Careers? Avoid These 5 Classic Mistakes

The average person can expect to change careers (not just jobs) 3 to 5 times in their working life. Avoid the 5 classic mistakes most career and job changers make.

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Most of the experts say that the average person can expect to change careers (not just jobs) 3 to 5 times in their working life. The reasons? Many people are burnt-out, underpaid, stressed out, bored, unsatisfied, or at a career dead end. For some, their careers have changed on them –thanks to corporate mergers, changes in technology, company restructuring, age discrimination, and a thousand other reasons. After counseling thousands of people in finding new careers and jobs, we have found that there are 5 classic mistakes most career and job changers make:

MISTAKE 1: NO CLEAR GOAL.

Not having a clear goal is like trying to run a race when you do not know where the finish line is. Many career changers have only a partial goal. They KNOW that they want a job with less stress, or more money, or more of a future, or more independence, or more satisfaction. A career goal, however, should be comprehensive, specific, clear, and realistic. It should include not only the practicalities of your situation, but also who you are, the realities of the job market, and the potential pitfalls.

MISTAKE 2: NO CLEAR PICTURE OF YOUR STRENGTHS.

Most career changers (and job seekers) spend more time worrying about their weaknesses than their strengths. Most people don’t even know what their strengths are. But it is your strengths–not your weaknesses–that determine your career success. Get a professional assessment. This should also include your personal characteristics, motivation, aptitudes, goals, values, interests, and talents. A career and job decision is too important not to have this picture.

MISTAKE 3: NO CAREFUL PLANNING.

Sure, most people think about it for a long time, but thinking is not the same thing as detailed planning. Most people plan a night out with friends more carefully than they plan their careers. Planning would mean researching the new career, talking to people who are in the new career, getting some hands-on experience, reading (books, trade journals, industry newsletters), developing strategies for any possible negatives or problems, consulting with a mentor, knowing what education or training you would need, and other actions.

MISTAKE 4: NO MOTIVATION.

As a psychologist who has worked with underachievers of all ages, I can tell you that many have good intentions but fail to take action. This is, of course, a normal human trait. There are times when all of us procrastinate, give ourselves excuses, and do not do the things that will lead us to our goals. If you are changing careers, however, you had better be motivated. Only consistent, daily, well-considered action will get you where you want to go.

MISTAKE 5: NO INDIVIDUALIZED JOB SEARCH STRATEGY.

If you are changing careers, you need something more than the usual job search tactics. You need a strategy that fits who you are as a unique individual and the fact that you are changing careers. For example, if you tell a job interviewer (or anyone else) that you are “changing careers,” it is the kiss of death. You see, if you are changing careers, then you are starting over–from square one–and are competing with kids just out of school. Instead, you should say, “I am taking the next step in my career” (which, actually, is closer to the truth for most career changers). Another example: Make sure your résumé is rewritten so that it doesn’t “lock you in” to the old career. Go light on the jargon. Emphasize skills in the old career that would be a real advantage (not just “transferable skills”) in the new career. If you avoid these classic mistakes, you are well on your way to making a successful job and career change.

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Manual Handling Course Online – More Than Just for Safety

Are you wondering whether it is possible to take a manual handling course online? If so, you should know that not only manual handling training but also you can take a Patient handling course Dublin online. Apart from these two courses, you can take many other work-related courses online. When it comes to Online manual handling training, you might think that this course will teach you how to safely do manual handling tasks.

Indeed, this course and many other work-related courses like Online abrasive wheels training and Online Fire Safety training will help you in more ways than safety alone. Yes, these work-related courses will help you gain a better edge among the crowd of applicants when you apply for a new job irrespective of the industry you wish to apply.

How Can Work-Related Courses Help in Other Ways?
Let us consider that you take an online first aid course. Not only in factories but also in any industry, having a person who has undergone first aid training will be beneficial. The reason is that when there is a person, who has undergone first aid training, he will handle any injuries and health hazards to one of the employees and even non-employees in an organization before medical help arrives. In turn, he can be of great help in saving precious lives.

Also, after two years of completing the first aid course, you can take the Online FAR training. This refresher course will refresh your knowledge of the old and new first aid techniques. When you take the PHECC FAR course, it will be even more beneficial as you can gain a competitive edge when you are a PHECC-Certified first aider.

Benefits Specific to Manual Handling Training Online:
When other work-related courses mentioned above can be beneficial, as you can understand, taking the Elearning manual handling training will help you get other benefits as well like those mentioned below:

The Manual Handling Course online will provide you with the skill of safe manual handling that will help you as a life skill.
The Online manual handling training courses will help you get the right relief from your back pain. If you have done manual handling tasks earlier, you very well know the back pain that improper manual handling tasks can cause. Thanks to the courses that will teach you how to prevent back pains when you engage in manual handling tasks.
Conclusion:
in short, not only for ensuring your safety and for the safety of others in your workplace, you should take work-related courses to gain a better edge when competing with fellow candidates for a new job.

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Data Cleaning Techniques: Learn Simple & Effective Ways To Clean Data

In this article, we will learn about the different data cleaning techniques and how to effectively clean data using them. Each technique is important and you also learn something new.

Top Data Cleaning Techniques to Learn
Let’s understand, in the following paragraphs, the different data cleaning techniques.

Remove Duplicates
The likelihood of having duplicate entries increases when data is collected from many sources or scraped. People making mistakes when keying in the information or filling out forms is one possible source of these duplications.

All duplicates will inevitably distort your data and make your analysis more difficult. When trying to visualize the data, they can also be distracting, so they should be removed as soon as possible.

Remove Irrelevant Data
If you’re trying to analyze something, irrelevant info will slow you down and make things more complicated. Before starting to clean the data, it is important to determine what is important and what is not. When doing an age demographic study, for instance, it is not necessary to incorporate clients’ email addresses.

There are various other elements that you would want to remove since they add nothing to your data. They include URLs, tracking codes, HTML tags, personally identifiable data, and excessive blank space between text.

Standardize Capitalization
It is important to maintain uniformity in the text across your data. It’s possible that many incorrect classifications would be made if capitalization were inconsistent. Since capitalization might alter the meaning, it could also be problematic when translating before processing.

Text cleaning is an additional step in preparing data for processing by a computer model; this step is much simplified if all of the text is written in lowercase.

Convert Data Types
If you’re cleaning up your data, converting numbers is probably the most common task. It’s common for numbers to be incorrectly interpreted as text, although computers require numeric data to be represented as such.

If they are shown in a readable form, your analytical algorithms will be unable to apply mathematical operations because strings are not considered numbers. Dates that are saved in a textual format follow the same rules. All of them need to be converted into numbers. For instance, if you have the date January 1, 2022, written down, you should update it to 01/01/2022.

Clear Formatting
Data that is overly structured will be inaccessible to machine learning algorithms. If you are compiling information from several resources, you may encounter a wide variety of file types. Inconsistencies and errors in your data are possible results.

Any pre-existing formatting should be removed before you begin working on your documents. This is typically a straightforward operation; programs like Excel and Google Sheets include a handy standardization feature.

Fix Errors
You’ll want to eliminate all mistakes from your data with extreme caution. Simple errors can cause you to lose out on important insights hidden in your data. Performing a simple spell check can help avoid some of these instances.

Data like email addresses might be rendered useless if they contain typos or unnecessary punctuation. It may also cause you to send email newsletters to those who have not requested them. Inconsistencies in formatting are another common source of error.

A column containing just US dollar amounts, for instance, would require a conversion of all other currency types into US dollars to maintain a uniform standard currency. This also holds for any other unit of measurement, be it grams, ounces, or anything else.

Language Translation
You’ll want everything to be written in the same language so that your data is consistent. Also, most data analysis software is limited in its ability to process many languages because of the monolingual nature of the Natural Language Processing (NLP) models upon which it is based. In that case, you’ll have to do a complete translation into a single language.

Handle Missing Values
There are two possible approaches to dealing with missing values. You can either input the missing data or eliminate the observations that contain this missing value. Your decision should be guided by your analysis objectives and your intended use of the data.

The data may lose some valuable insights if you just eliminate the missing value. You probably have your reasons for wanting to retrieve this data in mind. It may be preferable to fill in the blanks by determining what should be entered into the relevant fields. If you don’t recognize it, you can always substitute “missing.” If it’s a number, just type “0″ into the blank. However, if too many values are missing to be useful, the entire section should be eliminated.

Conclusion
We reach the final parts of the article, having discussed 8 highly important data cleaning techniques professionals must know about. These techniques make your job easier to deal with data, removing unwanted ones. If you feel data and numbers are where you feel at ease, data science is the ideal career path for you.

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