@include('includes.header')

<script src="{{  url('js/country.js')  }}"></script>
<script>
    $(window).bind("pageshow", function() {
        // update hidden input field
    });
</script>
<section class="resheight" style="background:#007BFF" >
    <div id="particles-js" style="background: url({{ url('images/internship.jpeg') }}); background-size: 100% 100%;"></div>
</section>

<div id='loadingDiv' style='display:none;'>

</div>
{{--<section id="common-title" style="">--}}
    {{--<div class="container">--}}
        {{--<p class="animated zoomInDown associate-title-font" style="" >Internship Registration form--}}
        {{--</p>--}}
        {{--<!--<hr style="padding: 0;margin: 0;background: rgba(255,255,255,0.6)">-->--}}
    {{--</div>--}}
{{--</section>--}}
<section class="workshop-section">
    <div class="container padding0 " style="padding: 0 5px;">
	<span style="">The Department of Computer Science Engineering at Bennett university is offering a winter internship of 4 weeks under the initiative of LeadingIndia.Ai. The internship starts on 27th May 2019. During the 4 weeks internship, you will be actively working on a Deep Learning based project. In the first week, we will host a crash course for you to cover the basic concepts related to Deep Learning. In the further weeks, you will be engaged with a researcher to work on an end-to-end Deep Learning project.</span><br><br>      
		<div class="col-sm-12 padding0 text-justify">
				<span>These are some of the broad areas on which you will pursue your Deep Learning projects:</span>
            <ol>
                <li>Object Recognition and Detection </li>
                <li>Natural Language Processing</li>
                <li>Unusual Activity Detection </li>
                <li>Cyber Fraud Detection</li>
                <li>Real-time Video Processing</li>
            </ol>
		</div>
		<div class="col-sm-12 padding0 text-justify"><br>
		<p style="font-weight:600">About the Internship</p>
            <span>Selected intern's day-to-day responsibilities include</span>
            <ol>
                <li> Use web-based (or other) APIs to scrape relevant data</li>
                <li> Perform preprocessing and curate datasets for machine learning tasks</li>
                <li>Use different ML/DL techniques to perform prediction/regression tasks as required by the problem statement</li>
                <li>Fine-tune your models and hyper-parameters in order to achieve the best performance as per the defined goals</li>
                <li>Put the different pieces of your ML/DL code together to create an end-to-end product</li>
                <li>Work with live projects from Industry/startups to contribute to the ongoing AI revolution</li>
            </ol>
		</div>
		<div class="col-sm-12 padding0 text-justify">
		<p style="font-weight:600">
			 <b>Skill(s) required </b>: Proficiency in at least one coding language is necessary. Python is highly preferred, but not mandatory.  </p>

		   </div>
		<div class="col-sm-12 padding0 text-justify">
		<p style=" ">
			 <b>Who can apply</b>: <br>
                Only those candidates can apply who:
            <ol>
                <li> are available for full time (in-office) internship</li>
                <li> can start the internship from 27th May'19 </li>
                <li>are available for duration of 4 weeks</li>
                <li> have relevant skills and interests</li>
            </ol>
        </p>

		   </div>
		<div class="col-sm-12 padding0 text-justify">
		<p style=" ">
            If you want to avail the hostel/mess facility of Bennett University, kindly make a payment via <a
                    href="https://leadingindia.ai/internship"> https://leadingindia.ai/internship</a> to Bennett University as per the details given below. The amount for 4 weeks (which includes hostel, laundry and food & snacks) is Rs. 18000/-. For anyone who wants to stay longer (for the purpose of satisfying the internship requirements of your University), the amount will be Rs. 600/- per day.
        </p>
            <p style="font-weight: 600;">
                (Note: This includes the registration charges for three-day exhaustive workshop on Deep Learning.)
            </p>
            <p>
                It is highly recommended that you stay in the hostel so that you can devote full energy towards your project and obtain full benefit from the Internship.
            </p>
            <p>
                In a special case, if someone does not need the hostel facility, then you need to pay Rs. 3000/- (Non-refundable amount) which includes the registration charges for the three-day workshop on Deep Learning.
            </p>
            <p>
                You should complete the above-mentioned payments by 30th Oct 2019. Please note that this payment window has been specially created to consider last-minute internship requests, and no extensions will be possible.

                While making the payment, put "<b>Winter Internship</b>" in the '<b>Description</b>'.

                After making the payment, please share its screenshot with me on email @madhushi.verma@bennett.edu.in
            </p>
            <p>
                If you fail to show up for the internship or quit midway, no refunds would be possible.
            </p>
            <p>For any other queries, please write to madhushi.verma@bennett.edu.in.</p>
		   </div>
    </div>
</section>

@include('includes.footer')


<script src="{{  url('js/particles.js')  }}"></script>
<script src="{{  url('js/app.js')  }}"></script>

<script>
    var count_particles, stats, update;
    stats = new Stats;
    stats.setMode(0);
    stats.domElement.style.position = 'absolute';
    stats.domElement.style.left = '0px';
    stats.domElement.style.top = '0px';
    document.body.appendChild(stats.domElement);
    count_particles = document.querySelector('.js-count-particles');
    update = function() {
        stats.begin();
        stats.end();
        if (window.pJSDom[0].pJS.particles && window.pJSDom[0].pJS.particles.array) {
            count_particles.innerText = window.pJSDom[0].pJS.particles.array.length;
        }
        requestAnimationFrame(update);
    };
    requestAnimationFrame(update);
</script>


<script>

    $(document).ready(function(){

        var scrollTop = 0;
        var widthWindow = 0;
        $(window).scroll(function(){
            scrollTop = $(window).scrollTop();
            $('.counter').html(scrollTop);
            if (scrollTop >= 10) {
                widthWindow = $(window).width();
                if(widthWindow >=768){
//                    $('#global-nav').addClass('scrolled-nav');
                    $('#global-nav').css('background','#007BFF');
                }

            } else if (scrollTop < 40) {
                $('#global-nav').removeClass('scrolled-nav');
            }

        });

    });


</script>

<script src="{{  url('js/paper.min.js')  }}"></script>
<script src="{{  url('js/bootstrap.min.js')  }}"></script>
</body>
</html>