<div dir="ltr"><div>Dear Community/Scientists/Professors/Researchers,<br><br>Greetings of the day!!<br><br>(Apologies in case of multiple receptions)<div> <br>Launching a self-paced training on Linear Machine Learning, Generative AI for data science project building and Creating Docker containers for Machine learning devops.<br><br>More info: <a href="https://internships.utkarshminds.com/courses/Python-Statistics-Data-analysis-and-Generative-AI-Combination-66c9b728d5db276fc548a735" rel="noreferrer" target="_blank">https://internships.utkarshminds.com/courses/Python-Statistics-Data-analysis-and-Generative-AI-Combination-66c9b728d5db276fc548a735</a><div><br></div><div>Fees: $14 (EUR 14.75) or ₹ 800<br><br><div><strong>Why Should You Enroll?</strong><br></div><div><div><ul><li style="margin-left:15px"><strong>Comprehensive Curriculum:</strong> Learn practical and theoretical aspects of Python</li><li style="margin-left:15px"><strong>Expert Guidance:</strong> Get trained by professionals with extensive experience in the field.</li><li style="margin-left:15px"><strong>Affordable Fees:</strong> Gain valuable skills </li><li style="margin-left:15px"><strong>Career Advancement:</strong> Enhance your resume and improve your job prospects.</li></ul><p><strong>Contact Details:</strong> Pranav Nerurkar<br></p><p>Email: <a rel="noreferrer noreferrer">pranav.nerurkar@utkarshminds.com</a><br>Phone: +919619997797</p></div><div><h3><span style="font-size:small;font-weight:normal">Key Features:</span><br></h3><ol><li style="margin-left:15px"><p><strong>Interactive Video Lectures</strong>:</p><ul><li style="margin-left:15px">Learn the fundamentals of Two Sample Hypothesis Testing through engaging and informative video lectures.</li><li style="margin-left:15px">Understand key concepts such as null and alternative hypotheses, t-tests, z-tests, p-values, and confidence intervals.</li></ul></li><li style="margin-left:15px"><p><strong>Hands-On Coding Assignments</strong>:</p><ul><li style="margin-left:15px">Apply the theoretical knowledge gained from the lectures by completing coding assignments in languages such as Python or R.</li><li style="margin-left:15px">Work on real datasets to practice setting up hypotheses, running statistical tests, and interpreting results.</li><li style="margin-left:15px">Get step-by-step guidance on writing and debugging code to ensure accurate and efficient analysis.</li></ul></li><li style="margin-left:15px"><p><strong>Practical Applications</strong>:</p><ul><li style="margin-left:15px">Explore various case studies and examples that illustrate the application of Two Sample Hypothesis Testing in different fields such as healthcare, finance, marketing, and more.</li><li style="margin-left:15px">Engage in projects that mimic real-life scenarios where hypothesis testing is crucial for decision-making.</li></ul></li><li style="margin-left:15px"><p><strong>Mentorship and Support</strong>:</p><ul><li style="margin-left:15px">Receive mentorship from experienced statisticians and data scientists.</li><li style="margin-left:15px">Participate in Q&A sessions and discussion forums to clarify doubts and enhance your learning experience.</li></ul></li><li style="margin-left:15px"><p><strong>Certification</strong>:</p><ul><li style="margin-left:15px">Earn a certificate upon successful completion of the internship, showcasing your skills and knowledge in Two Sample Hypothesis Testing.</li><li style="margin-left:15px">Add this valuable credential to your resume or LinkedIn profile to boost your career prospects.</li></ul></li></ol><h4>Requirements:</h4><ul><li style="margin-left:15px">Basic understanding of statistics and programming.</li><li style="margin-left:15px">A computer with internet access.</li><li style="margin-left:15px">Willingness to learn and apply new concepts.</li></ul><h4>Duration:</h4><ul><li style="margin-left:15px">The course is self-paced and can be completed within 4-6 weeks, depending on your schedule and pace of learning.</li></ul><h4><span style="font-weight:normal">Warm and Kind regards,</span></h4></div></div></div></div></div><div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><table border="0" cellspacing="0" cellpadding="0" style="background-image:initial;background-position:initial;background-repeat:initial"><tbody><tr style="color:rgb(34,34,34)"><td style="padding:0cm"><table border="0" cellspacing="0" cellpadding="0"><tbody><tr><td width="189" style="width:5cm;padding:0cm"><p class="MsoNormal"><b><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif;color:black">Pranav A. NERURKAR</span></b><u></u></p><font color="#000000" face="Arial, sans-serif"><span style="font-size:12px">Specialist - AI & Data science</span></font><br><font color="#000000" face="Arial, sans-serif"><span style="font-size:12px">UTKARSH MINDS</span></font></td><td width="15" style="width:11.45pt;padding:0cm"></td><td width="3" style="width:2pt;border-top:none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