Course Description
Embark on an enlightening journey into the transformative fields of Machine Learning, Deep Learning, and Data Science with our comprehensive training course tailored for both newcomers and seasoned professionals. This program elucidates core concepts and delves into cutting-edge techniques indispensable for processing vast data, drawing actionable insights, and crafting predictive as well as complex deep learning models.
By the conclusion of this course, participants will be armed with the requisite skills to make data-driven decisions, fashion intricate predictive and deep learning models, and position themselves at the cusp of the next technological revolution. Whether you’re contemplating a career shift or aiming to bolster your existing skill set, this course promises to chart a robust trajectory in the dynamic domain of data and technology
What you’ll learn:
– Fundamental Concepts: Grasp the underpinnings of machine learning, deep learning, and data science, understanding their distinctions and real-world applications.
– Data Processing & Analysis: Acquire proficiency in techniques to clean, process, and analyze extensive datasets using renowned tools and libraries.
– Predictive Modelling & Deep Learning: Dive deep into a plethora of algorithms, spanning from regression models to advanced neural architectures like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). Gain hands-on experience in training, evaluating, and optimizing these models.
– Real-world Projects: Engage actively in practical projects addressing genuine business challenges, refining decision-making processes, and predicting future trends using advanced deep learning models.
Who This Course is for
This course is open to all and can be studied on its own as a standalone course or along with other I.T related courses on our platform.
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Project 1
This will focus on all concepts learned from weeks 1-8. Students will go through a robust end to end data science project on selected topic
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Week 1 - 2
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Week 3 - 4
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Week 5 - 6
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Week 7 - 8
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Week 9 - 10
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Week 11 - 12
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Project 2
This will focus on all concepts learned from week 9 - 12
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Week 13 - 14
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Week 15
DevOps
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Week 16 - 17
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Week 18 - 19
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Week 20 - 21
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Week 22 - 23
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Week 24