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Data Analysis with Python Mini Bootcamp will teach you the fundamental skills of Python, SQL, Statistics and an introduction to machine learning. With those skills, you will be ready to take any kind of data science boot-camp or you\u2019ll be ready to start learning data science on your own. During our prep course you will explore a hands-on experience that will ignite your enthusiasm and confidence to learn data science and its\u2019 theory.[\/vc_column_text]<\/div>
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\u25cf <\/span>Week 2: <\/p>\n \u25cf <\/span>Week 3: <\/p>\n \u25cf <\/span>Week 4: The 12 hours of schedule is as follows:<\/p>\n <\/p>\n March 16 \u2013 23 \u2013 30 and April 6 <\/p>\n Data Analysis with Python Mini Bootcamp <\/span>has a $300 tuition fee.<\/p>\n For the \u201cEarly Bird\u201d applicants (January 15 \u2013 March 9), the tuition fee is $250.<\/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> <\/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_row][vc_column width=”1\/4″][\/vc_column][vc_column width=”1\/4″][\/vc_column][vc_column width=”1\/4″][\/vc_column][vc_column width=”1\/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=”11410″ 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-4039","page","type-page","status-publish","hentry"],"yoast_head":"\n
\n1. Read and write data from\/to different formats (excel, csv, text, etc.)
\n2. Cleanse and select important records from Dataframes
\n3. Deal with missing data: identify, replace, and eliminate records
\n4. Sort Dataframes by multiple columns<\/p>\n
\n1. Leverage the functions apply, lambda, filter, and map
\n2. Merge\/Join Dataframes by foreign keys
\n3. Learn pivot tables in Pandas<\/p>\n
\n1. Learn data visualizations with the libraries Matplotlib and Seaborn
\n2. Introduction to the Machine Learning library Sklearn
\n3. Apply linear and logistic regression with Sklearn[\/vc_column_text]<\/div>
\nMondays, from 6:30 pm to 9:30 pm[\/vc_column_text]<\/div>