career mentor

I hope this week’s episode leaves you with interview pointers you can put into practice the next time you find yourself gearing up for interviews.

Music:
Song: Sun Never Sets
Music by: CreatorMix.com

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In this episode, I share 5 tips on Defining Your Professional Brand. I want you to learn how to effectively articulate your value so that you can navigate to your desired career goals. 

Please visit my LinkedIn page Career Chats with LaKeisha using the following link to download a free worksheet to help you define your Professional Brand Statement and follow my page: https://www.linkedin.com/feed/update/urn:li:activity:6985463620184788993

Music:
Song: Sun Never Sets
Music by: CreatorMix.com

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This episode is all about going into detail on 5 tips that will equip you to navigate corporate America with ease. My 5 tips for decoding the corporate game are:

1. Get A Mentor
2. Be Self-Aware
3. Build Relationships 
4. Get Used to Conflict
5. Seek Exposure

Song: Sun Never Sets
Music by: CreatorMix.com

LinkedIn: https://www.linkedin.com/company/careerchatswithlakeisha/
Instagram: @careerchatswithLaKeisha

My podcast introduction, my story, and my why!

Song: Sun Never Sets
Music by: CreatorMix.com

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As the COVID-19 corona virus outbreak continues to spread across the globe, companies and researchers are looking to use artificial intelligence as a way of addressing the challenges of the virus. A number of research projects are using AI to identify drugs that were developed to fight other diseases but which could now be repurposed to take on corona virus. By studying the molecular setup of existing drugs with AI, companies want to identify which ones might disrupt the way COVID-19 works.

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Digital Transformation is the use of new, fast and frequently changing digital technology to solve problems. One of the examples of digital transformation is cloud computing. It reduces reliance on user owned hardware and increases reliance on subscription based cloud services.

 Digital transformation will bring success to you largely because of its speed and accuracy –especially when digital disruption are snapping at the heels of many businesses. Let’s explore the incredible benefits that digital transformation will bequeath on business and its workforce.

To speak in interviews, you must have a proven portfolio on Data Science Projects to Showcase in your resume as well as to speak damn confident in interviews.

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AI has increased in the last five years because new machine learning techniques are solving particular problems in ways that are similar to humans and with comparable accuracy like playing games (reinforcement learning), reading and understanding natural language (text analytics), and analyzing images and videos (convolutional neural networks or CNNs).
To speak in interviews, you must have a proven portfolio on Data Science Projects to Showcase in your resume as well as to speak damn confident in interviews.

If you are planning to learn a Data Science Program based on the above job requirements enroll for our Data Science Career Transition Program(YDSCT30)
⛔️ 30% Discount: https://www.bepec.in/data-science-car...

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 Major Difference between AI/ML Engineer & Data Scientist. Actually, there are multiple parameters you can differentiate these two professionals and if you are looking to hire machine learning engineer and shortlisting the data scientist you need to know the actual difference between these two AI specialists. Machine learning is a branch of artificial intelligence where a class of data driven algorithms enables software applications to become highly accurate in predicting outcomes without any need for explicit programming.

  If you want to become a ML engineer you may have options like either continue working as entry level programmer or explore the opportunities into AI filed and become a specialist in big data or machine learning programmer to develop an AI model. 

 If you are ambitious to become a data scientist, you need to gain more education as master/doctorate degree to make your academic skills more strong and gain the capability to analyze and utilize the data for deep learning.

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 Neural networks is one of the most powerful and widely used algorithms when it comes to the sub field of machine learning called deep learning. The neural networks that we are going to considered are strictly called artificial neural networks, and as the name suggests, are based on what science knows about the human brain’s structure and function.

 Briefly, a neural network is defined as a computing system that consist of a number of simple but highly interconnected elements or nodes called Neurons , which are organized in layers which process information using dynamic state responses to external inputs. This algorithm is extremely useful, as we will explain later, in finding patterns that are too complex for being manually extracted and taught to recognize to the machine.

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 These days, one of the biggest concerns in the corporate world is the need to grow in your job. As the corporate world is getting competitive every minute, many of us are trying too hard to stay in the league.

 You can also create enough opportunities by building a network within your workplace. Venture out with your team lead and coworkers often, strike healthy conversations at lunch, or call for quick meetings during break times. Discussing official as well as unofficial ideas can help you setup a structured network.

We from BEPEC are ready to help you and make you shift your career at any cost.
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Q & A Session with Recent placed participants. Thank you Swetha & Lakme for your advice to our learners & making the Data science Interview Preparation session wonderful!! To Know More Join Our Career Transition Program Enroll now!! call @9121516181

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  As demand for data scientist skills remains strong, hiring for these positions poses a challenge.

 Data science overlaps with the growing field of artificial intelligence (AI). To function at their full potential, AI applications require data lots of it. In fact  many of the following AI and data science skills from programming languages to algorithmic techniques work in tandem with one another r building on top of each other to garner deeper data insights. Consequently, as the demand for data scientists increases the discipline presents an enticing career path for students and existing professionals.

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Are you looking to get a break in data science but struggling to clear interviews?  There’s a ton of variance in interview questions. You will get the IBM interview process which from what we have heard is really high level questions like, describe how a decision tree works? or Describe how this works or that works?

You should think about the interview process as being similar to an important test at school: if you walk into interview without preparing, you are probably going to be in trouble. When answering any interview question you should have three goals in mind  Be clear, Be concise and Answer appropriately. Mastering the first, be clear, is mostly about preparation. You can only explain something clearly when you know what you’re talking about. Being concise is about carefully listening to and answering the question, but not more and Answering appropriately  just requires you keep in mind who you’re talking to. Are you speaking to a data scientist with 15 years of experience? and use as much jargon as you want.

 We from BEPEC are ready to help you and make you shift your career at any cost.
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 Major Assets of an AI Engineer, AI Engineers build, test, and deploy AI models as well as maintain the underlying AI infrastructure. They are problem solvers who can navigate between traditional software development and machine learning implementations.

In a nutshell, machine learning is a relatively novel approach at solving some problems in the computer science that were traditionally hard to solve such as for example, building a program that will successfully recognize handwritten text. Machine learning is founded on algorithms that parse large sets of data and learn from this data, without being programmed in the traditional sense of the word  that is without relying on a series of steps but rather learning from the data that is fed into machine learning algorithms.

 An AI Engineer also needs to understand both traditional and agile approach in software development life cycle including continuous integration, continuous delivery and continuous deployment (CI/CD). They also must understand various testing practices including test driven development and behavior driven development.

We from BEPEC are ready to help you and make you shift your career at any cost.
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 There are many skills under the umbrella of data science, and we should not expect any one single person to be a master of them all. To become a data scientist requires a candidate to possess expert skills in various fields like software development, database query languages, machine learning, programming, mathematics, statistics, data visualization, etc. This seems like a lot and many do get discouraged once they go through this immense list of skills that they are told is necessary to become a data scientist. 

 This learning enables the program to think, decide and do work based on programmed instruction sets. The prerequisites for learning exciting Artificial Intelligence technologies are Strong hold on Mathematics,Strong experience of programming languages,Writing algorithm for finding patterns and learning,strong data analytics skills,Good knowledge of Discrete mathematics and Strong will to learn machine learning languages.

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 Are you looking to get a break in data science but struggling to clear interviews? Well the process starts right from the stage you start researching the different roles that interest you. And it goes all the way up to the completion of in person interviews.

 If you’re applying to hundreds of jobs and not getting any interviews, though, there’s a good chance that something is wrong. It could be that you’re not qualified for the jobs you are applying to or it could be that something in your application materials is bothering recruiters. To make matters more complicated, unlike software development positions which have more standardized interview processes, data science interviews can have huge variations. This is partly because as an industry, there still isn’t an agreed upon definition of a data scientist into three paths: Algorithms, Inference and Analytics.

We from BEPEC are ready to help you and make you shift your career at any cost.
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 Machine Learning’s inroads into our collective consciousness have captured our imaginations. If you are interested in learning machine learning skills to enter this field, your moment is now. Majorly there are 4 properties or characteristics or measurements scales decide the whole depth and breadth of a machine learning project.

 The key distinction has to do with the end goal. As a Data Analyst, you’re analyzing data in order to tell a story and to produce actionable insights for members of your team. The analysis is performed and presented by human beings to other human beings who may then go on to make business decisions based on what’s been presented. The “audience” for your output is human. As a Machine Learning engineer on the other hand, your final “output” is working software (not the analyses or visualizations that you may have to create along the way), and your “audience” for this output often consists of other software components that run autonomously with minimal human supervision.

The world is unquestionably changing in rapid and dramatic ways, and the demand for Machine Learning engineers is going to keep increasing exponentially. If this is YOUR future, then there’s no time like the present to start mastering the skills and developing the mindset you’re going to need to succeed.

We from BEPEC are ready to help you and make you shift your career at any cost.
Anyone are interested for Career Transition Programs on ML / AI / DL / Data Science
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Finding a career mentor can be straightforward and easy with the four easy steps talked about it in this episode. 

For more information, go to www.anitabelitz.com.

Having a career mentor can make a huge difference in your career. Find out why you should have one, regardless of what level you are in your organization.

For more information, go to www.anitabelitz.com.