<\/p>\n

We will then learn how unstructured text data is structured so that it can be analyzed and assimilated with structured data. We will then learn how collections of documents can be summarized, clustered and classified for a deeper, high-level understanding of the documents and concepts embedded in them. Next, we will explore search engineering which allows efficient exploration of collections of documents. Finally, we will see how graph databases can help bring diverse text data into a coherent linking of the data collection where visualization is leveraged to help glean insights.<\/p>\n

 <\/p>\n

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

 <\/p>\n

\n
• Anyone who is interested in entering the world of NLP and do not know where to start.<\/li>\n
• Anyone who wants an introduction to ML\/Deep Learning and how to apply it to NLP<\/li>\n
• Anyone who is interested in building NLP applications in Python<\/li>\n
• Anyone who wants to understand how commonly used NLP applications are built<\/li>\n<\/ul>\n

   <\/p>\n

  Course Requirements:<\/p>\n

   <\/p>\n

  \n
  • Having an interest in learning Natural Language Processing and data science is enough to take this course.<\/li>\n
  • This course has no prior coding experience requirement.<\/li>\n<\/ul>\n[\/vc_column_text]<\/div>
    [vc_column_text]What will you learn?<\/strong><\/p>\n

     <\/p>\n

    \u25cf Working with Test Data in Python
    \n\u25cf Regular Expressions
    \n\u25cf Text processing with NLTK and Spacy
    \n\u25cf POS Tagging
    \n\u25cf NER Tagging
    \n\u25cf Text Normalization
    \n\u25cf Stemming
    \n\u25cf Lemmatization
    \n\u25cf Topic Modeling
    \n\u25cf Interpreting Patterns
    \n\u25cf LDA
    \n\u25cf LSA (Latent Semantic Analysis)
    \n\u25cf Feature Engineering for Text
    \n\u25cf Bag of Words
    \n\u25cf TF-IDF
    \n\u25cf SVD
    \n\u25cf Word Embedding
    \n\u25cf Identify Topics in Text
    \n\u25cf Text Classification
    \n\u25cf Deep Learning for NLP
    \n\u25cf Project
    \n\u25cf Auto. Tagging
    \n\u25cf Article Categorize
    \n\u25cf Social Media Info. Extract
    \n\u25cf Spam Classification
    \n<\/span>[\/vc_column_text]<\/div>

    [vc_column_text]Start learning the NLP for Non-Coders with outside of business hours schedule!<\/p>\n

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

     <\/p>\n

    March 17 \u2013 24 \u2013 31 and April 7<\/p>\n

    Tuesdays, from 6:30 pm to 9:30 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]NLP for Non-Coders 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 for Non-Coders Mini Bootcamp has a $300 tuition fee.
    \nFor the \u201cEarly Bird\u201d applicants (January 15<\/span> \u2013 March 10), 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]Paul Starrett is a licensed private investigator (CA, IL) and attorney (CA) specializing in high-profile investigations and legal consulting especially where electronic data is central. He is founder and CEO of Starrett Consulting, Inc., a full-service investigations firm that leverages API\u2019s from open-source and commercial data-science applications to analyze structured and unstructured data. He is former General Counsel and Chief Global Risk Officer of an international, publicly-held data management corporation heading their global legal, operations and risk-management groups. His 25 year career began in law enforcement and corporate security and later progressed into information-security engineering, electronic discovery and information management. Paul’s education includes a Master of Science in Predictive Analytics from Northwestern University and a Master of Laws (LL.M.) in Taxation from Golden Gate University. He is also a Certified Fraud Examiner (CFE) and EnCase Certified Computer Forensics Examiner (EnCE).[\/vc_column_text]<\/div><\/div>[\/vc_column][\/vc_row]\n<\/div>","protected":false},"excerpt":{"rendered":"

    [vc_row][vc_column width=”1\/4″][\/vc_column][vc_column width=”3\/4″][\/vc_column][\/vc_row][vc_row][vc_column css=”.vc_custom_1532675419863{padding-right: 0px !important;padding-left: 0px !important;}”][vc_empty_space height=”23px”][vc_single_image image=”11420″ img_size=”full”][vc_empty_space height=”20px”][\/vc_column][\/vc_row][vc_row][vc_column][\/vc_column][\/vc_row]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1464,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"_mi_skip_tracking":false,"footnotes":""},"class_list":["post-10260","page","type-page","status-publish","hentry"],"yoast_head":"\n