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Google is Hiring Software Engineering Intern

Minimum qualifications:

Preferred qualifications:

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About the job

Our Summer internships start in May/June 2022 and are 10-12 weeks in duration.

As a Software Engineering Intern, you will work on our core products and services as well as those who support critical functions of our engineering operations. Depending on your background and experience, you will be working in these area:

Product and Systems Development

Whether it's finding new and innovative ways to advance search quality, building computing platforms and networking technologies, automating the indexing of videos, or continuing to refine and scale complex auction systems, you'll develop solutions for challenging technical problems. You will research, conceive and develop software applications to extend and improve on Google's product offerings and collaborate on scalability issues involving access to massive amounts of data and information.

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CISCO is Hiring Intern

What You’ll Do (Role details)

The CSS is a hands-on expert for their aligned product or architecture. This role owns delivery of targeted engagements intended to increase product awareness, share industry leading practices, and drive overall product consumption and business value.

The CSS brings strategic vision and tactical expertise to ensure every customer engagement is a success while also actively participating in the global CSS Community where they collaborate with their peers to share best practices and customer success stories.

The CSS is able to effectively combine deep technical knowledge with solid understanding of business priorities to provide consultative solutions pivotal to helping customers realize value faster.

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Who You Are

Recent graduate or on your final year of studies towards a Bachelor's or Master's degree in a technical field, such as Networking, Computer Science, Information Technology, Electrical/Computer Engineering or a similar field

• Minimum GPA of 8.5 and above
• The requirement is for 2022 passout only
• Fluent in English (verbal and written)
• Passionate about networking, information technology or computer science
• Strong analytical and problem-solving skills with ability to troubleshoot technical problems
• Ability to multi-task, self-start, and work in a fast-paced team environment and the ability to work independently

Why Cisco

WeAreCisco, where each person is unique, but we bring our talents to work as a team and make a difference powering an inclusive future for all.

We embrace digital, and help our customers implement change in their digital businesses. Some may think we’re “old” (36 years strong) and only about hardware, but we’re also a software company. And a security company. We even invented an intuitive network that adapts, predicts, learns and protects. No other company can do what we do – you can’t put us in a box!

But “Digital Transformation” is an empty buzz phrase without a culture that allows for innovation, creativity, and yes, even failure (if you learn from it.)

Day to day, we focus on the give and take. We give our best, give our egos a break, and give of ourselves (because giving back is built into our DNA.) We take accountability, bold steps, and take difference to heart. Because without diversity of thought and a dedication to equality for all, there is no moving forward.

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Google Offers Free Online Course on Machine Learning, Check Important Details

Google has offered a free online course on machine learning that can be taken by interested participants. The course called “Machine Learning Crash Course with TensorFlow APIs” is Google’s fast-paced, practical introduction to machine learning that can be completed in 15 hours. The Google free online machine learning crash course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.

The course requires interested participants to have a basic knowledge of machine learning, NumPy, pandas, algebra, trigonometry, calculus, and so on. If participants are new to machine learning, they can also take an Introduction to Machine Learning Problem Framing being provided by Google. The one-hour self-study course teaches participants how to identify appropriate problems for machine learning.

Prerequisites to Take Google Free Online Course on Machine Learning

The course does not mandate for candidates to have any prior knowledge in machine learning. However, to understand the concepts presented and complete the exercises, students will need to meet the following prerequisites:

• Participants must be comfortable with variables, linear equations, graphs of functions, histograms, and statistical means.
• Participants should be good programmers, and ideally, have some experience programming in Python because the programming exercises are in Python. However, experienced programmers without Python experience can usually complete the programming exercises anyway, says Google.

What the Google Free Online Course on Machine Learning Will Cover?

After completing the course, participants will be able to recognize the practical benefits of mastering machine learning, and understand the philosophy behind machine learning. Some of the topics that will be covered are as follows:

• Introduction to machine learning.
• Framing.
• Descending into machine learning.
• Reducing loss.
• Define common machine learning terms.
• Describe examples of products that use machine learning and general methods of machine learning problem-solving used in each.
• Identify whether to solve a problem with machine learning.

• Compare and contrast machine learning to other programming methods.
• Apply hypothesis testing and the scientific method to machine learning problems.
• Have conversations about machine learning problem-solving methods and so on.

Those who wish to know more and take the Google free online course on machine learning are advised to visit the official website for details.

Some of the questions answered in this course

1. How does machine learning differ from traditional programming?
2. What is loss, and how do I measure it?
3. How does gradient descent work?
4. How do I determine whether my model is effective?
5. How do I represent my data so that a program can learn from it?
6. How do I build a deep neural network?

Accelerators

Google Developers' regional accelerators are tailored specifically to their local markets and provide access to the best of Google—its people, network, and advanced technologies—helping startups build great products. Using the knowledge gained from running startup accelerators, this model has been used to reach other audiences such as game developers and non-profits.

Descending into ML: Linear Regression

It has long been known that crickets (an insect species) chirp more frequently on hotter days than on cooler days. For decades, professional and amateur scientists have cataloged data on chirps-per-minute and temperature. As a birthday gift, your Aunt Ruth gives you her cricket database and asks you to learn a model to predict this relationship. Using this data, you want to explore this relationship.

As expected, the plot shows the temperature rising with the number of chirps. Is this relationship between chirps and temperature linear? Yes, you could draw a single straight line like the following to approximate this relationship:

Learn and apply fundamental machine learning concepts with the Crash Course, get real-world experience with the companion Kaggle competition, or visit Learn with Google AI to explore the full library of training resources.