<\/p>\n

Who this course is for:<\/p>\n

\n
• Anyone who is comfortable writing Python code, using loops, lists, dictionaries, etc.<\/li>\n
• Anyone who want to learn more about machine learning<\/li>\n
• Anyone with interest in Natural Language Processing and it’s applications<\/li>\n<\/ul>\n

  Course Requirements:<\/p>\n

  \n
  • Basic knowledge in python coding<\/li>\n
  • Basic knowledge in Machine Learning<\/li>\n
  • Basic knowledge in linear algebra and probability<\/li>\n<\/ul>\n[\/vc_column_text]<\/div>
    [vc_column_text]What will you learn?<\/strong><\/p>\n

     <\/p>\n

    \u25cf <\/span>Week 1:<\/p>\n

    \n
    1. Introduction to the course and expectations\n
       \n
       1. What is NLP?<\/li>\n
       2. Examples of NLP in the real world<\/li>\n
       3. What to expect from this course?<\/li>\n
       4. NLP Workflow<\/li>\n<\/ol>\n<\/li>\n
       5. Basics of language processing & understanding text\n
          \n
          1. Regular Expressions for text processing<\/li>\n
          2. Scraping Websites<\/li>\n
          3. NLTK and spaCy<\/li>\n
          4. Tokens, Lemmas<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

              <\/p>\n

             \u25cf <\/span>Week 2:<\/p>\n

             \n
             1. Supervised Learning Models for Text Data\n
                \n
                1. Bag of Words with Classification Models<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

                    <\/p>\n

                   \u25cf <\/span>Week 3:<\/p>\n

                   \n
                   1. Unsupervised Learning Models for Text Data\n
                      \n
                      1. TFIDF<\/li>\n
                      2. Latent Semantic Analysis<\/li>\n
                      3. Dimension Reduction<\/li>\n<\/ol>\n<\/li>\n
                      4. Unsupervised neural network\n
                         \n
                         1. Introduction to word2vec<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

                             <\/p>\n

                            \u25cf <\/span>Week 4:<\/p>\n

                            \n
                            1. Build your own NLP Model\n
                               \n
                               1. A hands-on project<\/li>\n<\/ol>\n<\/li>\n
                               2. An introduction to Advanced NLP topics<\/li>\n<\/ol>\n[\/vc_column_text]<\/div>
                                  [vc_column_text]Start learning the NLP with outside of business hours schedule!<\/p>\n

                                  The 12 hours of schedule is as follows:<\/p>\n

                                   <\/p>\n

                                  March 15 \u2013 22 \u2013 29 and April 5
                                  \nSundays, from 9:00 am to 12:00 pm[\/vc_column_text]<\/div>

                                  [vc_column_text]The venue for the bootcamp is Magnimind Academy Sunnyvale Campus: 830 Stewart Dr #182, Sunnyvale, CA 94085. The capacity is limited to 20 people.[\/vc_column_text]<\/div>

                                  [vc_column_text]Natural Language Processing Mini Bootcamp is now also available online. Anyone who wants to attend this mini bootcamp can join online live webinars where the same course content will be taught. Online sessions will be distributed through zoom conferences. Students will have access to the screen of the instructor, external camera showing class atmosphere, whiteboard, and be able to ask questions through chat. You may attend this mini bootcamp no matter where you are.[\/vc_column_text]<\/div>

                                  [vc_column_text]Tuition fee<\/b><\/p>\n

                                   <\/p>\n

                                  NLP (Natural Language Processing) Mini Bootcamp has a $300 tuition fee.
                                  \nFor the \u201cEarly Bird\u201d applicants (January 15<\/span> \u2013 March 8), the tuition fee is $250.<\/span><\/p>\n

                                   <\/p>\n

                                  Payment process<\/b><\/p>\n

                                   <\/p>\n

                                  After you finish filling your application form, the website will direct you to the payment page. There, you can select available payment options.<\/p>\n

                                   <\/p>\n

                                  Cancellation<\/b><\/p>\n

                                   <\/p>\n

                                  If you\u2019re not satisfied with the course you may cancel your application.\u00a0<\/span>[\/vc_column_text]<\/div>

                                  [vc_column_text]Course Application<\/b><\/p>\n

                                   <\/p>\n

                                  The application process starts at magnimindacademy.com. You can view the course pages and learn more about your intended course. You can apply by clicking the \u201cBuy now\u201d button and then fill out the application form.[\/vc_column_text]<\/div>

                                  [vc_column_text]Murali Mandayam is a passionate customer engagement and customer success leader who has managed engineering teams across the globe having worked for companies like Intellisync and Nokia. Murali has delivered several SaaS-based projects for companies such as Sprint, RIM-Blackberry, AOL, Microsoft and embedded IoT applications for major European and US-based automotive OEMs, in-vehicle infotainment platform companies, and medical and set-top box device makers.<\/p>\n

                                   <\/p>\n

                                  Prior to relocating to Silicon Valley Murali was spearheading a Fintech application company in Hong Kong and Tokyo, Japan.<\/p>\n

                                   <\/p>\n

                                  Along with his technical and people management skills, Murali was also managing the P&L of his group where he was building regular analytics reports using tools such as Tableau and QlikView that triggered his interests in data analytics and data science. Murali has since completed a rigorous course in Data Science becoming proficient in Python and its various machine learning libraries such as supervised, unsupervised modeling techniques, and NLP.<\/p>\n

                                   <\/p>\n

                                  Murali is currently heading the US operations for Claysol Media Labs, an embedded and full-stack engineering company headquartered in Bangalore India and also consults on data science and data analytics projects for Bay Area companies.<\/p>\n

                                   <\/p>\n

                                  Murali holds a Master\u2019s degree in Computer Science from Birla Institute of Technology and Science, a leading technical institute in India that collaborates with MIT and Ford Foundation.[\/vc_column_text]<\/div><\/div>[\/vc_column][\/vc_row]\n<\/div>","protected":false},"excerpt":{"rendered":"

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