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<P style="MARGIN: 5px 15px" align=center><FONT style="FONT-SIZE: 14pt"
color=#ffffff face=Arial>C U R S O</FONT></P></TD></TR>
<TR>
<TD bgColor=#ffff00><FONT color=#ffff00 face=Arial>
<DIV
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align=center><B><FONT size=7 face=Calibri>PLANEAMIENTO DE LA DEMANDA CON
INTELIGENCIA ARTIFICIAL</FONT></B></DIV></FONT></TD></TR>
<TR>
<TD bgColor=#ff8040>
<P style="MARGIN: 10px 15px" align=center><B><FONT face=Arial>21 y
22 de Enero de 7pm a 10pm (horario GMT-5)<BR></FONT><FONT size=2
face=Arial>Vía Zoom en vivo - Incluye consultas en vivo a los expertos,
grabaciones, materiales y certificado</FONT></B></P></TD></TR>
<TR>
<TD>
<DIV align=center> <STRONG><FONT color=#ff0000>¡<FONT
face=Calibri>APROVECHE LA PROMO 4X2!</FONT></FONT></STRONG></DIV>
<DIV><SPAN
style="FONT-SIZE: small; FONT-FAMILY: Calibri; WHITE-SPACE: normal; WORD-SPACING: 0px; TEXT-TRANSFORM: none; FLOAT: none; FONT-WEIGHT: 400; COLOR: rgb(255,0,0); FONT-STYLE: normal; ORPHANS: 2; WIDOWS: 2; DISPLAY: inline !important; LETTER-SPACING: normal; BACKGROUND-COLOR: rgb(255,255,255); TEXT-INDENT: 0px; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial; font-variant-ligatures: normal; font-variant-caps: normal"><FONT
color=#ffffff size=2>clubactuarialitammx</FONT></SPAN></DIV></TD></TR>
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<P style="MARGIN-BOTTOM: 10px; MARGIN-TOP: 10px"
align=center><B><FONT color=#ffffff face=Arial><SPAN
style="TEXT-DECORATION: none"><A
href="https://api.whatsapp.com/send?phone=51965282222&text=Solicito%20mayor%20informaci%C3%B3n%20del%20curso%20Planeamiento%20de%20DemandaIA%20em"><FONT
color=#ffffff><SPAN style="TEXT-DECORATION: none">MAYOR
INFORMACIÓN<BR>CLIC
AQUI</SPAN></FONT></A></SPAN></FONT></B></P></TD></TR></TBODY></TABLE></DIV><FONT
color=#ffffff>clubactuarialitammx</FONT></TD></TR>
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face=Calibri></FONT></SPAN></P>
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face=Calibri></FONT></SPAN></SPAN></FONT>
<DIV
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<P
style="BOX-SIZING: border-box; FONT-SIZE: 14px; FONT-FAMILY: Roboto, sans-serif; WHITE-SPACE: normal; WORD-SPACING: 0px; TEXT-TRANSFORM: none; FONT-WEIGHT: 400; COLOR: rgb(44,54,58); FONT-STYLE: normal; TEXT-ALIGN: left; ORPHANS: 2; WIDOWS: 2; MARGIN: 0px 0cm 7.5pt; LETTER-SPACING: normal; BACKGROUND-COLOR: rgb(255,255,255); TEXT-INDENT: 0px; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial; font-variant-ligatures: normal; font-variant-caps: normal"
align=justify><SPAN
style="BOX-SIZING: border-box; FONT-FAMILY: Calibri, sans-serif"><FONT
face=Arial>El planeamiento de demanda es un proceso clave en las
organizaciones y la tecnología permite automatizar el proceso
especialmente en la parte de análisis estadístico. Sin embargo, cada día
hay mas importancia en la data reciente y futuro, generada por eventos muy
recientes y futuros que deben incorporarse al proceso para crear el plan
de demanda. La inteligencia artificial IA es el reemplazo del ser humano
en procesos operativos y de toma de decisiones y en este caso, la parte
estadística esta casi resuelta por medio de sistemas como Streamline que
se utilizará en el curso. La parte de información reciente por redes
sociales y algoritmos que modifiquen el pronóstico es clave y para ello la
tecnología permite crear redes neuronales que aprenden y crean modelos mas
precisos de planes de demanda con IA.</FONT></SPAN></P><SPAN
style="BOX-SIZING: border-box; FONT-FAMILY: Calibri, sans-serif">
<P
style="BOX-SIZING: border-box; FONT-SIZE: 14px; FONT-FAMILY: Roboto, sans-serif; WHITE-SPACE: normal; WORD-SPACING: 0px; MARGIN-TOP: 0px; TEXT-TRANSFORM: none; FONT-WEIGHT: 400; COLOR: rgb(44,54,58); FONT-STYLE: normal; TEXT-ALIGN: left; ORPHANS: 2; WIDOWS: 2; LETTER-SPACING: normal; BACKGROUND-COLOR: rgb(255,255,255); TEXT-INDENT: 0px; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial; font-variant-ligatures: normal; font-variant-caps: normal"><BR
style="BOX-SIZING: border-box"><B
style="BOX-SIZING: border-box; FONT-WEIGHT: bolder"><SPAN
style="BOX-SIZING: border-box; COLOR: rgb(0,51,102)"><FONT
face=Arial>CONTENIDO:</FONT></SPAN></B></SPAN></P>
<P
style="BOX-SIZING: border-box; FONT-SIZE: 14px; FONT-FAMILY: Roboto, sans-serif; WHITE-SPACE: normal; WORD-SPACING: 0px; MARGIN-TOP: 0px; TEXT-TRANSFORM: none; FONT-WEIGHT: 400; COLOR: rgb(44,54,58); FONT-STYLE: normal; TEXT-ALIGN: left; ORPHANS: 2; WIDOWS: 2; LETTER-SPACING: normal; BACKGROUND-COLOR: rgb(255,255,255); TEXT-INDENT: 0px; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial; font-variant-ligatures: normal; font-variant-caps: normal"><B
style="BOX-SIZING: border-box; FONT-WEIGHT: bolder"><SPAN
style="BOX-SIZING: border-box; FONT-FAMILY: Calibri, sans-serif; COLOR: red"><FONT
face=Arial>1. FUNDAMENTOS DE INTELIGENCIA ARTIFICIAL<BR
style="BOX-SIZING: border-box"></FONT></SPAN></B><SPAN
style="BOX-SIZING: border-box; FONT-FAMILY: Calibri, sans-serif"><FONT
face=Arial>a. Fundamentos de IA<SPAN> </SPAN><FONT
color=#ffffff>clubactuarialitammx</FONT><BR style="BOX-SIZING: border-box">b.
Redes neuronales<SPAN> </SPAN><FONT color=#ffffff>]</FONT><BR
style="BOX-SIZING: border-box">c. Nuevas tecnologías aplicadas: Visión
artificial, robótica, sensores y dispositivos IoT<BR
style="BOX-SIZING: border-box"><BR
style="BOX-SIZING: border-box"></FONT><FONT face=Arial><B
style="BOX-SIZING: border-box; FONT-WEIGHT: bolder"><SPAN
style="BOX-SIZING: border-box; COLOR: red">2. FUNDAMENTOS DE PLANEAMIENTO
DE LA DEMANDA<BR style="BOX-SIZING: border-box"></SPAN></B>a. Principios
de la demanda y el proceso de 4 etapas<BR
style="BOX-SIZING: border-box">b. Componentes de un buen pronóstico:
estadístico y aleatorio<BR style="BOX-SIZING: border-box">c. Importancia
de crear un modelo de gestión de demanda<BR
style="BOX-SIZING: border-box"><BR
style="BOX-SIZING: border-box"></FONT><FONT face=Arial><B
style="BOX-SIZING: border-box; FONT-WEIGHT: bolder"><SPAN
style="BOX-SIZING: border-box; COLOR: red">3. AUTOMATIZANDO EL PROCESO CON
STREAMLINE<BR style="BOX-SIZING: border-box"></SPAN></B>a. Implementación
del software Streamline<BR style="BOX-SIZING: border-box">b. Revisión de
datos a cargar al sistema<BR style="BOX-SIZING: border-box">c.
Automatización del modelo: uso de STREAMLINE<BR
style="BOX-SIZING: border-box">d. Uso de IA en el
proceso<SPAN> </SPAN><FONT color=#ffffff>clubactuarialitammx</FONT><BR
style="BOX-SIZING: border-box"></FONT><B
style="BOX-SIZING: border-box; FONT-WEIGHT: bolder"><BR
style="BOX-SIZING: border-box"><SPAN
style="BOX-SIZING: border-box; COLOR: red"><FONT face=Arial>4. ALGORITMOS
DE IA PARA DETECTAR PATRONES DE COMPORTAMIENTO EN LA DEMANDA HISTÓRICA<BR
style="BOX-SIZING: border-box"></FONT></SPAN></B><FONT face=Arial>a. Lumpy
demand: comportamiento de demanda histórica erratica<BR
style="BOX-SIZING: border-box">b. Short history: casos de productos
nuevos<STRONG style="BOX-SIZING: border-box; FONT-WEIGHT: bolder"><SPAN
style="BOX-SIZING: border-box; FONT-FAMILY: Calibri, sans-serif; COLOR: white">v</SPAN></STRONG><BR
style="BOX-SIZING: border-box">c. Outliers: eliminación de picos y valles
en la data histórica<BR style="BOX-SIZING: border-box">d. Sparse history:
casos de demanda histórica dispersa<SPAN> </SPAN><FONT
color=#ffffff>clubactuarialitammx</FONT><BR style="BOX-SIZING: border-box">e.
Model change: casos de cambios en el comportamiento de la demanda<BR
style="BOX-SIZING: border-box">f. Negative trend: comportamiento histórica
de demanda con tendencia negativa<BR style="BOX-SIZING: border-box">g.
Slow Move Products SMP: productos de baja rotación<BR
style="BOX-SIZING: border-box"><BR
style="BOX-SIZING: border-box"></FONT><FONT face=Arial><B
style="BOX-SIZING: border-box; FONT-WEIGHT: bolder"><SPAN
style="BOX-SIZING: border-box; COLOR: red">5. ALGORITMOS DE PRONÓSTICO DE
DEMANDA BASADA EN PROMEDIOS Y SUAVIZACIÓN<BR
style="BOX-SIZING: border-box"></SPAN></B>a. Fundamentos estadísticos<BR
style="BOX-SIZING: border-box">b. Promedio móvil simple<BR
style="BOX-SIZING: border-box">c. Promedio móvil ponderado<BR
style="BOX-SIZING: border-box">d. Suavizamiento exponencial<BR
style="BOX-SIZING: border-box">e. TaIIer 1: casos para desarrollar
pronósticos con promedios y suavización<BR
style="BOX-SIZING: border-box">f. TaIIer 2: STREAMLINE, carga de datos,
modificaciones, exportación<BR style="BOX-SIZING: border-box"><BR
style="BOX-SIZING: border-box"></FONT><FONT face=Arial><B
style="BOX-SIZING: border-box; FONT-WEIGHT: bolder"><SPAN
style="BOX-SIZING: border-box; COLOR: red">6. ¿CÓMO SELECCIONAR EL MEJOR
MODELO DE PRONÓSTICO?<BR style="BOX-SIZING: border-box"></SPAN></B>a.
Exactitud del pronóstico: mediciones del error<BR
style="BOX-SIZING: border-box">b. Indicador de exactitud MAD Mean Average
Deviation<BR style="BOX-SIZING: border-box">c. Indicador de exactitud MAPE
Mean Average Percentage Error<BR style="BOX-SIZING: border-box">d. TaIIer
3: casos de selección del mejor modelo de pronóstico<BR
style="BOX-SIZING: border-box"><BR
style="BOX-SIZING: border-box"></FONT><FONT face=Arial><B
style="BOX-SIZING: border-box; FONT-WEIGHT: bolder"><SPAN
style="BOX-SIZING: border-box; COLOR: red">7. CAMBIOS AL PRONÓSTICO
ESTADÍSTICO: MARKET INTELLIGENCE Y MARKET RESEARCH<BR
style="BOX-SIZING: border-box"></SPAN></B>a. Cambios en el proceso por la
IA<BR style="BOX-SIZING: border-box">b. Creando un sistema de market
intelligence<BR style="BOX-SIZING: border-box">c. Metodologías de búsqueda
de información: market research<BR style="BOX-SIZING: border-box">d.
Implementación de algoritmos en una red neuronal de planificación de
demanda<BR style="BOX-SIZING: border-box">e. TaIIer 4: diseño del proceso
de demanda<BR style="BOX-SIZING: border-box"><BR
style="BOX-SIZING: border-box"></FONT><FONT face=Arial><B
style="BOX-SIZING: border-box; FONT-WEIGHT: bolder"><SPAN
style="BOX-SIZING: border-box; COLOR: red">8. PRONÓSTICO DE DEMANDA BASADO
EN REGRESIÓN LINEAL SIMPLE<BR style="BOX-SIZING: border-box"></SPAN></B>a.
Fundamentos estadísticos<BR style="BOX-SIZING: border-box">b. Modelo de
regresión lineal simple<BR style="BOX-SIZING: border-box">c. Coeficiente
de correlación y determinación R2<BR style="BOX-SIZING: border-box">d.
TaIIer 5: casos de pronósticos con regresión lineal simple.
STREAMLINE</FONT></SPAN></P>
<P
style="BOX-SIZING: border-box; FONT-SIZE: 14px; FONT-FAMILY: Roboto, sans-serif; WHITE-SPACE: normal; WORD-SPACING: 0px; MARGIN-TOP: 0px; TEXT-TRANSFORM: none; FONT-WEIGHT: 400; COLOR: rgb(44,54,58); FONT-STYLE: normal; TEXT-ALIGN: left; ORPHANS: 2; WIDOWS: 2; LETTER-SPACING: normal; BACKGROUND-COLOR: rgb(255,255,255); TEXT-INDENT: 0px; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial; font-variant-ligatures: normal; font-variant-caps: normal"><B
style="BOX-SIZING: border-box; FONT-WEIGHT: bolder"><SPAN
style="BOX-SIZING: border-box; FONT-FAMILY: Calibri, sans-serif; COLOR: red"><FONT
face=Arial>9. CASOS ESPECIALES DE PRONÓSTICOS DE DEMANDA<BR
style="BOX-SIZING: border-box"></FONT></SPAN></B><FONT face=Arial><SPAN
style="BOX-SIZING: border-box; FONT-FAMILY: Calibri, sans-serif">a. <FONT
face=Arial>Pronósticos de demanda con estacionalidad</FONT><BR
style="BOX-SIZING: border-box">b. <FONT face=Arial>Pronósticos basados en
un modelo de regresión múltiple</FONT><BR
style="BOX-SIZING: border-box">c. <FONT face=Arial>Estrategias para la
gestión de la incertidumbre</FONT><BR style="BOX-SIZING: border-box">d.
<FONT face=Arial>TaIIer 6: casos especiales de
pronóstico</FONT></SPAN> </FONT></P>
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