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3	3	* ((( ==== **[[Beginner >>||anchor = "HBeginner-1"]]** ==== )))
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	5	+* ((( ==== **[[Intermediate >>||anchor = "HIntermediate-1"]]** ==== )))
	6	+
5	5	=== **Beginner** ===
6	6
7	7	=== [[Creating a simple cell optimisation>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/simplecell/simplecell.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
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14	14	**Level**: beginner(%%) **Type**: interactive tutorial
15	15
16	16	This notebook will explain how to optimise a model using the covariance matrix adaptation (CMA) optimisation strategy. BluePyOpt includes two flavors of CMA: a single objective one and a hybrid single/multi objective one.
	19	+=== [[Optimising synaptic parameters>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/expsyn/ExpSyn.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
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	21	+**Level**: beginner(%%) **Type**: interactive tutorial
	22	+
	23	+This notebook shows how the parameters of a NEURON point process (in this case a synapse), can be optimised using BluePyOpt.
	24	+=== **Intermediate** ===
	25	+
	26	+=== [[Creating an optimisation with meta parameters>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/metaparameters/metaparameters.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
	27	+
	28	+**Level**: intermediate(%%) **Type**: interactive tutorial
	29	+
	30	+This notebook will explain how to set up an optimisation that uses metaparameters (parameters that control other parameters)
	31	+=== [[Setup of a cell model with multi electrode simulation for local field potential recording>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/l5pc_lfpy/L5PC_LFPy.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
	32	+
	33	+**Level**: intermediate(%%) **Type**: interactive tutorial
	34	+
	35	+This notebook will demonstrate how to instantiate a cell model and evaluator that include local field potential (LFP) computation and its recording using a simulated multi electrode array (MEA).
	36	+=== [[Exporting a cell in the neuroml format and running it>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/neuroml/neuroml.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
	37	+
	38	+**Level**: intermediate(%%) **Type**: interactive tutorial
	39	+
	40	+In this tutorial we will go over how to export a cell to neuroml, create a LEMS simulation able to run the neuroml cell and then how to run the simulation.
	41	+=== [[Tsodyks-Markram model of short-term synaptic plasticity>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/tsodyksmarkramstp/tsodyksmarkramstp.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
	42	+
	43	+**Level**: intermediate(%%) **Type**: interactive tutorial
	44	+
	45	+In this notebook we demonstrate how to fit the parameters of the Tsodyks-Markram model to a given in vitro somatic recording. The in vitro trace used here shows a typical L5TTPC-L5TTPC depressing connection, kindly provided by Rodrigo Perin (EPFL).
	46	+=== [[Optimization of burst and tonic firing in thalamo-cortical neurons>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/thalamocortical-cell/thalamocortical-cell_opt.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
	47	+
	48	+**Level**: intermediate(%%) **Type**: interactive tutorial
	49	+
	50	+In this tutorial we will go over how to set up the cell model and the cell evaluator, run an optimisation and how to analyse optimisation results.
	51	+