Python is becoming the preferred language for data scientists and developers who use advanced analytics and machine learning in their work. Python is increasingly being used in a wide range of applications such as data science, web development, artificial intelligence, and more. This machine learning course is designed to provide an introduction to the Python language, machine learning tools, and related algorithms.
By the end of the course, the student will be able to confidently use Python for machine learning applications. Students will also learn about a variety of machine learning algorithms and frameworks such as deep learning, natural language processing, and support vector machines. There will be an emphasis on practical application as the students will be exposed to different use cases and projects that use machine learning in order to get hands-on experience. The course will also cover topics related to problem solving, communication, and the code optimization process.
Flexible Dates
Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.4-Hour Sessions
Training never been so convenient- attend training sessions 4-hour long for easy learning.Destination Training
Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.Live Online Training (Duration : 40 Hours) | |||
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1. Basic understanding of coding fundamentals
2. Basic understanding of Python language (variables, loops, functions)
3. Familiarity with popular scientific computing libraries (NumPy, SciPy, Matplotlib, Pandas, etc.)
4. Understanding of basic machine learning concepts (linear and logistic regression, basic neural networks, supervised and unsupervised machine learning techniques)
Python for Machine Learning training is ideal for individuals who are interested in furthering their career in the field of data science and software engineering. This training is suitable for people who have experience with programming and a basic knowledge of statistics and calculus.
The training is also beneficial for students and academics who are studying machine learning and are generally interested in furthering their knowledge in this field. Research scientists in data science and computer-based intelligence can also gain benefit from this training.
Furthermore, this workshop can be helpful for anyone who is curious about machine learning and AI, or anyone from a business that may develop a machine learning tool or application in the future.
In summary, this training is suited for anyone that has a passion for machine learning or anyone who is looking to develop their knowledge in the area of machine learning, data science and AI.
1. Understand the core fundamentals of Python and its features.
2. Learn the principles of Machine Learning and its different types.
3. Introduction to Artificial Neural Networks, Convolutional Neural Networks, Deep Learning, and their respective theories.
4. Developing an in-depth knowledge of Python libraries such as NumPy, SciPy, pandas, and matplotlib.
5. Understand feature pre-processing, model evaluation, and tuning techniques.
6. Working with data types such as N-dimensional array, structured and unstructured data.
7. Introduction to supervised and unsupervised learning algorithms.
8. Understanding and practice of object-oriented programming with Python.
9. Data wrangling, cleaning, and pre-processing techniques.
10. Understanding machine learning models such as Support vector machines, Decision Trees, K-nearest neighbors, and Random forests.