昨晚我们生信技能树的学习大使 《二货潜》神神秘秘的甩给我一个GitHub资源链接,里面有一份非常好的数据分析学习资料:加拿大生物信息学研讨会 ,而且笃定我们生信技能树以前没有分享过。确实我在生信技能树写了1.3万篇教程,还真记不清楚我以前有没有分享过。但是最近我们就分享过两个类似的资源 :
学习资源真心是比想学习的人还多,不信你就看下去!说实话,写完公众号,我看到这个当时就傻眼了:
加拿大生物信息学研讨会资源宝藏 官方主页链接:
https://bioinformatics.ca/workshops/2018-epigenomic-data-analysis/ github 链接:
https://github.com/bioinformatics-ca twitter 主页:
https://twitter.com/bioinfodotca 各种主页:
https://bioinformaticsdotca.github.io/ youtube 链接:
https://www.youtube.com/channel/UCKbkfKk65PZyRCzUwXOJung 最重要:有视频、有讲义 PDF以及PPT 、有实战,并且都是讲的特别详细。** **放在最前面的话,我觉得讲义看
2019的就行了。如果加上视频比较好理解,那就看
2018`。**
容我打开 2019 资料网站:https://bioinformaticsdotca.github.io/
点进去界面是这样的:
再往下滑动:
好了,我们可以清楚的看到分为几大块。
2019 High-throughput Biology: From Sequence to Networks 这部分主要讲从序列到最终的调控网络,也包括了一些基础的 UNIX/R 的学习。(这部分 PDF 421 页)
准备工作: 1) R Preparation tutorials:
2) UNIX Preparation tutorials:
3) Sequencing Terminology
4) Cytoscape Preparation tutorials : Complete the introductory tutorial to Cytoscape
培训前需要查看的文献 Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration Genome structural variation discovery and genotyping A survey of sequence alignment algorithms for next-generation sequencing Genotype and SNP calling from next-generation sequencing data Informatics for RNA Sequencing: A Web Resource for Analysis on the Cloud Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown ENCODE RNA-Seq Standards Methods to study splicing from high-throughput RNA sequencing data A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium 接下来就是一周的课程安排 Module 1: Introduction to High-throughput Sequencing Module 2: Data Visualization Module 3: Genome Alignment Module 4: Small-Variant Calling and Annotation Module 5: Structural Variant Calling Module 6: De Novo Assembly Module 7: Introduction to RNA Sequencing Analysis Module 8: RNA-seq Alignment and Visualization Paper: Recurrent chimeric RNAs enriched in human prostate cancer identified by deep sequencing Module 9: Expression and Differential Expression Module 10: Reference Free Alignment Module 11: Isoform Discovery and Alternative Expression Module 12: Introduction to Pathway and Network Analysis Module 13: Finding Over-Represented Pathways Module 14: Network Visualization and Analysis with Cytoscape and Reactome Module 15: More Depth on Network and Pathway Analysis and Cytoscape Enrichment map Module 16: Gene Function Prediction Module 17: Regulatory Network Analysis Introduction to R 两天
Exploratory Analysis of Biological Data Using R 两天
Bioinformatics for Cancer Genomics 这部分PDF 316 + 49 + 52 页
这部分学癌症相关的应该是大有用处
Module 1: Introduction to Cancer Genomics Module 2: Ethics of Data Usage and Security Module 3: Databases and Visualization Tools Module 4: Genome Alignment Module 5: Genome Assembly- Module 6: Copy Number Variants Module 7: Somatic Mutations and Annotations Module 8: Gene Expression Profiling Module 9: Gene Fusion and Rearrangements Module 10: Genes to Pathways Module 11: Variants to Networks Module 12: Integration of Clinical Data Informatics for RNA-Seq Analysis 这部分就是我们最基础的 RNA-seq 分析所需要做的内容 这部分PDF 131 页
Module 1: Introduction to Cloud Computing Module 2: Introduction to RNA Sequencing Analysis Module 3: RNA-seq Alignment and Visualization Module 4: Expression and Differential Expression Module 5: Reference Free Alignment Module 6: Isoform Discovery and Alternative Expression Module 7: Genome Guided and Genome-Free Transcriptome Assembly Module 8: Functional Annotation and Analysis of Transcripts Informatics on High-Throughput Sequencing Data 这部分PDF 182 页
Module 1: Introduction to High-throughput Sequencing Module 2: Data Visualization Module 3: Genome Alignment Module 4: Small-Variant Calling and Annotation Module 5: Structural Variant Calling Module 6: De Novo Assembly Pathway and Network Analysis of -omics Data 这部分对于做调控网络的应该是大有帮助 这部分PDF 186 页
Module 1: Introduction to Pathway and Network Analysis Module 2 Finding Over-Represented Pathways Module 3: Network Visualization and Analysis with Cytoscape Module 4: More Depth on Network and Pathway Analysis Module 5: Gene Function Prediction Module 6: Regulatory Network Analysis Using Clouds for Big Cancer Data Analysis 上面就是 2019 年培训资料相关的。
当然这只是一部分。
2018
Informatics on High-Throughput Sequencing Data 2018 课程链接:https://bioinformaticsdotca.github.io/high-throughput_biology_2017
Day 1 Module 1: Introduction to High-throughput Sequencing Module 2: Data Visualization Module 3: Genome Alignment Day 2 Module 4: Small-Variant Calling and Annotation Module 5: Structural Variant Calling Module 6: De Novo Assembly Infectious Disease Genomic Epidemiology 2018 课程链接:https://bioinformaticsdotca.github.io/epidemiology_2018
Day 1 Module 1: Introduction to Public Health Microbiology and Genomic Epidemiology Module 2: Pathogen Genomic Analysis I Module 3: Pathogen Genomic Analysis II Day 2 Module 4: Antimicrobial Resistance Genes Module 5: Phylogeographic Analysis Day 3 Module 6: Emerging Pathogen Detection and Identification Using Metagenomics Samples Module 7: Data Visualization Informatics and Statistics for Metabolomics 2018 课程链接:https://bioinformaticsdotca.github.io/metabolomics_2018
Day 1 Module 1: Introduction to Metabolomics Module 2: Metabolite Identification and Annotation Module 3: Databases for Chemical, Spectral, and Biological Data Day 2 Module 4: Backgrounder in Statistics Module 5: MetaboAnalyst Module 6: Future of Metabolomics Pathway and Network Analysis of -Omics Data 2018 课程链接:https://bioinformaticsdotca.github.io/pathways_2018
Day 1 Module 1: Introduction to Pathway and Network Analysis Module 2: Finding Over-Represented Pathways Module 3: Network Visualization and Analysis with Cytoscape Day 2 Module 4: More Depth on Pathway and Network Analysis Module 5: Gene Function Prediction Day 3 Module 6: Regulatory Network Analysis Introduction to R 2018 课程链接:https://bioinformaticsdotca.github.io/intror_2018
Exploratory Analysis of Biological Data Using R 2018 课程链接:https://bioinformaticsdotca.github.io/eda_2018
Recording Session 1 Recording Session 2 Recording Session 3 Recording Session 4 Recording Session 5 Recording Session 6 Recording Session 7 Recording Session 8 Bioinformatics for Cancer Genomics 2018 课程链接:https://bioinformaticsdotca.github.io//bicg_2017
Day 1 Module 1: Introduction to cancer genomics Module 2: Databases and Visualization Tools Module 3a: Cancer Databases Module 3b: Visualization Tools Day 2 Module 4: Genome Alignment Module 5: Genome Assembly Module 6: Copy Number Variants Day 3 Module 7: Somatic Mutations and Annotations Module 8: Gene Expression Day 4 Module 9: Gene Fusion and Rearrangements Module 10: Sharing and Scaling a VM Day 5 Module 11: Working Reproducibly in the Cloud Module 12: Big Data Analytics in the Cloud Module 13: Genes to Pathways Day 6 Module 14: Variants to Networks Module 15: Clinical Data Integration Informatics for RNA-Seq Analysis 2018 课程链接:https://bioinformaticsdotca.github.io/rnaseq_2018
Day 1 Module 1: Introduction to RNA Sequencing and Analysis Module 2: RNA-seq alignment and visualization Day 2 Module 3: Expression and Differential Expression Module 4: Reference Free Alignment Day 3 Module 5: Genome-Free De Novo Transcriptome Assembly Module 6: Functional Annotation and Analysis of Transcripts Informatics on High-Throughput Sequencing Data 2018 课程链接:https://bioinformaticsdotca.github.io/htseq_2018
Day 1 Module 1: Introduction to High-throughput Sequencing Module 2: Data Visualization Module 3: Genome Alignment Day 2 Module 4: Small-Variant Calling and Annotation Module 5: Structural Variant Calling Module 6: De Novo Assembly Epigenomic Data Analysis 2018 课程链接:https://bioinformaticsdotca.github.io/epigenomics_2018
Day 1 Module 1: Introduction to ChIP Sequencing and Analysis Module 2: ChIP-Seq Alignment, Peak Calling, and Visualization Day 2 Module 3: Introduction to WGBS and Analysis Module 4: Downstream Analyses and Integrative Tools Analysis of Metagenomic Data 2018 课程链接:https://bioinformaticsdotca.github.io/metagenomics_2018
Day 1 Module 1: Introduction to Metagenomics Module 2: Marker Gene-Based Analysis Module 3: PICRUSt Day 2 Module 4: Metagenomic Taxanomic and Functional Composition Module 5: Pulling Genomes from Metagenomes Day 3 Module 6: Metatranscriptomics Module 7: Statistical Tests for Metagenomics Module 8: Biomarkers and Bringing It All Together 2017
High-Throughput Biology - From Sequence to Networks 2017 课程链接:https://bioinformaticsdotca.github.io/high-throughput_biology_2017
Day 1 Module 1: Introduction to High-throughput Sequencing Module 2: Data Visualization Module 3: Genome Alignment Day 2 Module 4: Small-Variant Calling and Annotation Module 5: Structural Variant Calling Module 6: De Novo Assembly Day 3 Module 7: Introduction to RNA Sequencing Analysis Module 8: RNA-seq Alignment and Visualization Day 4 Module 9: Expression and Differential Expression Module 10: Reference Free Alignment Module 11: Isoform Discovery and Alternative Expression Day 5 Module 12: Introduction to Pathway and Network Analysis Module 13: Finding Over-Represented Pathways Module 14: Network Visualization and Analysis with Cytoscape Day 6 Module 15: More Depth on Network and Pathway Analysis Module 16: Gene Function Prediction Day 6 Module 17: Regulatory Network Analysis Infectious Disease Genomic Epidemiology 2017 课程链接:https://bioinformaticsdotca.github.io/genomic_epidemiology_2017
Day 1 Module 1: Introduction to Public Health Microbiology and Genomic Epidemiology Module 2: Pathogen Genomic Analysis I Module 3: Pathogen Genomic Analysis II Day 2 Module 4: Antimicrobial Resistance Genes Module 5: Phylogeographic Analysis Day 3 Module 6: Emerging Pathogen Detection and Identification Using Metagenomics Samples Module 7: Data Visualization Bioinformatics of Genomic Medicine 2017 课程链接:https://bioinformaticsdotca.github.io/genomic_medicine_2017
Day 1 Module 1: Introduction and Patient Phenotyping and Genetic Disease Module 2: Introduction to Tools, Computing Infrastructure, and Data Module 3: Variant Annotation Module 4: Translating Research Workflows into Clinical Tests Day 2 Module 5: Available Epigenetics Data and Resources Module 6: Epigenetic Profiling in Disease Module 7: Patient Similarity Fusion Pathway and Network Analysis of -Omics Data 2017 课程链接:https://bioinformaticsdotca.github.io/pathways_2017
Day 1 Module 1: Introduction to Pathway and Network Analysis Module 2: Finding Over-Represented Pathways in Gene Lists Module 3: Network Visualization and Analysis with Cytoscape Day 2 Module 4: More Depth on Pathway and Network Analysis Module 5: Gene Function Prediction Day 3 Module 6: Regulatory Network Analysis Introduction to R 2017 课程链接:https://bioinformaticsdotca.github.io/IntroR_2017
Exploratory Analysis of Biological Data Using R 2017 课程链接:https://bioinformaticsdotca.github.io/EDA_2017
Day 1 Module 1: Exploratory Data Analysis Module 2: Regression Module 3: Dimension Reduction Day 2 Module 4: Clustering Module 5: Hypothesis Testing Bioinformatics for Cancer Genomics 2017 课程链接:https://bioinformaticsdotca.github.io//bicg_2017
Day 1 Module 1: Introduction to cancer genomics Module 2: Databases and Visualization Tools Day 2 Module 3a: Genome Alignment Module 3b: Genome Assembly Module 4: Copy Number Variants Day 3 Module 5: Somatic Mutations and Annotations Module 6: Gene Expression Day 4 Module 7: Gene Fusion and Rearrangements Module 8: Variants to Networks Day 5 Module 8: Variants to Networks Module 9: Clinical Data Integration Informatics for RNA-Seq Analysis 2017 课程链接:http://bioinformatics-ca.github.io/informatics_for_rna_seq_analysis_2016/
Day 1 Module 1: Introduction to RNA Sequencing and Analysis Module 2: RNA-seq alignment and visualization Day 2 Module 3: Expression and Differential Expression Module 4: Reference Free Alignment Module 5: Isoform discovery and alternative expression Day 3 Module 6: Genome-Free De Novo Transcriptome Assembly Module 7: Functional Annotation and Analysis of Transcripts Informatics on High-Throughput Sequencing Data 2017 课程链接:https://bioinformaticsdotca.github.io/htseq_2017
Day 1 Module 1: Introduction to High-throughput Sequencing Module 2: Data Visualization Module 3: Genome Alignment Day 2 Module 4: Small-Variant Calling and Annotation Module 5: Structural Variant Calling Module 6: De Novo Assembly Informatics and Statistics for Metabolomics 2017 课程链接:https://bioinformaticsdotca.github.io/metabolomics_2017
Day 1 Module 1: Introduction to Metabolomics Module 2: Metabolite Identification and Annotation Module 3: Databases for Chemical, Spectral, and Biological Data Day 2 Module 4: Backgrounder in Statisticss Module 5: MetaboAnalyst Module 6: Future of Metabolomics Epigenomic Data Analysis 2017 课程链接:https://bioinformaticsdotca.github.io/epigenomics_2017
Day 1 Module 1: Introduction to ChIP Sequencing and Analysis Module 2: ChIP-Seq Alignment, Peak Calling, and Visualization Day 2 Module 3: Introduction to WGBS and Analysis Module 4: Downstream Analyses and Integrative Tools Microbiome Summer School - Big Data Analytics for Omics Science 2017 课程链接:https://bioinformaticsdotca.github.io/mss_2017
Day 1 Plenary 1: GUTOME 1010 and Beyond Plenary 2: Microbiomes, Metagenomes, and Marker Genes Plenary 3: Metagenomics Analysis Day 2 Plenary 4: Microbiome Biomarker Discovery Plenary 5: Metatranscriptomics Day 3 Plenary 6: Host Genomics Applied to the Microbiome Plenary 7: Introduction to Machine Learning for Biological Data Day 4 Plenary 8: ElasticSearch to Facilitate Data Mining of Human Microbiome Databases Plenary 9: Algorithms for Mass Spectrometry Plenary 10: Efficient Multi-Locus Biomarker Discovery 2016 Pathway and Network Analysis of -Omics Data 2016 课程链接:http://bioinformatics-ca.github.io/pathway_and_network_analysis_of_omics_data_2016/
Day 1 Module 1: Introduction to Pathway and Network Analysis Module 2: Finding Over-Represented Pathways in Gene Lists Module 3: Network Visualization and Analysis with Cytoscape Day 2 Module 4: More Depth on Pathway and Network Analysis Module 5: Gene Function Prediction Day 3 Module 6: Regulatory Network Analysis Introduction to R 2016 课程链接:http://bioinformatics-ca.github.io/introduction_to_r_2016/
Day 1 Module 1: The R Environment Module 2: Programming Basics Module 3: Using R for Data Analysis Exploratory Analysis of Biological Data Using R 2016 课程链接:http://bioinformatics-ca.github.io/exploratory_analysis_of_biological_data_2016/
Day 1 Module 1: Exploratory Data Analysis Module 2: Regression Analysis Module 3: Dimension Reduction Day 2 Module 4: Clustering Analysis Module 5: Hypothesis Testing for EDA Bioinformatics for Cancer Genomics 2016 课程链接:http://bioinformatics-ca.github.io/bioinformatics_for_cancer_genomics_2016/
Day 1 Module 1: Introduction to cancer genomics Module 2.1: Databases and Visualization Tools Module 2.2: Logging into the Cloud Day 2 Module 3: Mapping and Genome Rearrangement Module 4: Gene Fusion Discovery Day 3 Module 5: Copy Number Alterations Module 6: Somatic Mutations Day 4 Module 7: Gene Expression Profiling Module 8: Variants to Pathways Part 1: How to annotate variants and prioritize potentially relevant ones Part 2: From genes to pathways Day 5 Network Analysis using Reactome
Informatics for RNA-Seq Analysis 2016 课程链接:http://bioinformatics-ca.github.io/informatics_for_rna_seq_analysis_2016/
Day 1 Module 0: Introduction to Cloud Computing Module 1: Introduction to RNA Sequencing and Analysis Module 2: RNA-seq alignment and visualization Day 2 Module 3: Expression and Differential Expression Module 4: Isoform discovery and alternative expression Module 5: Reference Free Alignment Informatics on High-Throughput Sequencing Data 2016 课程链接:http://bioinformatics-ca.github.io/informatics_on_high-throughput_sequencing_data_2016/
Day 1 Module 1: Introduction to HT-sequencing and Cloud Computing Module 2: Genome Alignment Module 3: Genome Visualization Module 4: De Novo Assembly Day 2 Module 5: Genome Variation Module 6: Genome Structural Variation Module 7: Bringing it Together with Galaxy Informatics and Statistics for Metabolomics 2016 课程链接:http://bioinformatics-ca.github.io/informatics_and_statistics_for_metabolomics_2016/
Day 1 Module 1: Introduction to Metabolomics Module 2: Metabolite Identification and Annotation Module 3: Databases for Chemical, Spectral, and Biological Data Day 2 Module 4: Backgrounder in Statistical Methods Module 5: MetaboAnalyst Module 6: Future of Metabolomics Epigenomic Data Analysis 2016 课程链接:http://bioinformatics-ca.github.io/epigenomic_data_analysis_2016/
Day 1 Module 1: Introduction to ChIP Sequencing and Analysis Module 2: ChIP-Seq Alignment, Peak Calling, and Visualization Day 2 Module 3: Introduction to WGBS and Analysis Module 4: Downstream Analyses and Integrative Tools Analysis of Metagenomic Data 2016 课程链接:http://bioinformatics-ca.github.io/analysis_of_metagenomic_data_2016/
Day 1 Module 1: Introduction to Metagenomics and Computing in the Cloud Module 2: Marker Gene-based Analysis of Taxonomic Composition Module 3: Introduction to PICRUSt Day 2 Module 4: Metagenomic Taxonomic Composition Module 5: Metagenomic Functional Composition Day 3 Module 6: Metatranscriptomics Module 7: Biomarker Selection 2015 High-Throughput Biology - From Sequence to Networks 2015 课程链接:http://bioinformatics-ca.github.io/high_throughput_biology_2015/
Day 1 Module 1: Overview of HT-sequencing & Cloud Computing Module 2: Reference Genome Alignment Module 3: Data Visualization Module 4: De Novo Assembly Day 2 Module 5: Small variant calling & annotation Module 6: Structural variation calling Module 7: Bringing it all Together: Galaxy Day 3 Module 8: Introduction to RNA sequencing and analysis Module 9: RNA-seq alignment and visualization Day 4 Module 10: Expression and Differential Expression Module 11: Isoform discovery and alternative expression Day 5 Module 12: Introduction to Pathway and Network Analysis Module 13: Finding over-represented pathways in gene lists Module 14: Cytoscape Intro, Demo and Enrichment Maps Day 6 Module 15: Depth on Pathway and Network Analysis Module 16: Gene Function Prediction Day 7 Module 17: Gene Regulation Network Analysis Introduction to R 2015 课程链接:http://bioinformatics-ca.github.io/introduction_to_r_2015/
Day 1 Module 1: First Steps Module 2: Programming Basics - Module 3: Using R for Data Analysis Exploratory Analysis of Biological Data Using R 2015 课程链接:http://bioinformatics-ca.github.io/EDA_in_r_2015/
Day 1 Module 1: Exploratory Data Analysis Module 2: Regression Analysis Module 3: Dimension Reduction Day 2 Module 4: Clustering Analysis Module 5: Hypothesis Testing for EDA Bioinformatics for Cancer Genomics 2015 课程链接:http://bioinformatics-ca.github.io/bioinformatics_for_cancer_genomics_2015/
Day 1 Module 1: Introduction to cancer genomics Module 2: Databases and Visualization Tools Day 2 Module 3: Alignment and Genome rearrangements Module 4: Gene Fusion Discovery Day 3 Module 5: Copy Number Alterations Module 6: Somatic Mutations Day 4 Module 7: Gene Expression Profiling Module 8: Variants to Pathways Day 5 Network Analysis using Reactome FI
Pathway and Network Analysis of Omics Data 2015 课程链接:http://bioinformatics-ca.github.io/pathway_and_network_analysis_2015/
Day 1 Module 1: Introduction to Pathway and Network Analysis Module 2: Finding over-represented pathways in gene lists Module 3: Cytoscape Intro, Demo and Enrichment Maps Day 2 Module 4: Depth on Pathway and Network Analysis Module 5: Gene Function Prediction Day 3 Module 6: Gene Regulation Network Analysis Informatics for RNA-Seq Analysis 2015 课程链接:http://bioinformatics-ca.github.io/rnaseq_analysis_2015/
Day 1 Module 1: Introduction to RNA sequencing and analysis Module 2: RNA-seq alignment and visualization Day 2 Module 3: Expression and Differential Expression Module 4: Isoform discovery and alternative expression Informatics on High-Throughput Data 2015 课程链接:http://bioinformatics-ca.github.io/high-throughput_sequencing_2015/
Day 1 Module 1: Overview of HT-sequencing & Cloud Computing Module 2: Reference-guided Genome Alignment Module 3: Data Visualization Module 4: De Novo Assembly Day 2 Module 5: Small variant calling & annotation Module 6: Structural variation calling Module 7: Bringing it all Together: Galaxy Informatics and Statistics for Metabolomics 2015 课程链接:http://bioinformatics-ca.github.io/informatics_and_statistics_for_metabolomics_2015/
Day 1 Module 1: Introduction to Metabolomics Module 2: Software for Metabolite ID and Quantification Module 3: Databases for Chemical, Spectral and bIological Data Day 2 Module 4: Backgrounder in Statistics Module 5: MetaboAnalyst Module 6: Future of Metabolomics 2013 主要是用 R 分析芯片数据和流式细胞数据 Microarray Data Analysis 课程链接是:
http://bioinformatics-ca.github.io/microarrays_2013/
Day 1 Module 1: Introduction to Microarrays and R
Lecture:
Module 1 pdf
Module 1 ppt
Module 1 mp4
Lab Practical:
Modules 1-3 Lab questionsModule 2: Quality Control of Microarrays
Lecture:
Module 2 pdf
Module 2 ppt
Module 2 mp4
Lab Practical:
Modules 1-3 Lab questions
Day 1 analysis scriptDay 2 Module 3: Statistical Analysis
Lecture:
Module 3 pdf
Module 3 ppt
Module 3 mp4
Clustering Slides
Lab Practical:
Modules 1-3 Lab questions
Status of R script at 11:55am
Status of R script at 12:33pm
Status of R script at 4:24pm
R script with MAS5Module 4: Beyond the Microarray Experiment
Lecture:
Module 4 pdf
Module 4 ppt
Module 4 mp4Flow Cytometry Data Analysis using R 课程链接是:
http://bioinformatics-ca.github.io/flow_cytometry_2013/
Day 1 Module 1: Introduction to Flow Cytometry Analysis in R
Lecture:
Module 1 pdf
Module 1 mp4Module 2: Exploring FCM data in R
Lecture:
Module 2 pdf
Module 2 mp4
Lab Practical:
Module 2 Lab
PlottingReference.R - reference, summary and tutorial for plot functions in R .Module 3: Preprocessing and Quality Assurance of FCM Data
Lecture:
Module 3 pdf
Module 3 mp4
Lab Practical:
Module 3 LabDay 2 Module 4: Automated Cell Population Identification
Lecture:
Module 4 pdf
Module 4 mp4Module 5: 1D Automated Gating
Lecture:
Module 5 pdf
Module 5 mp4
Lab Practical:
Module 5 LabModule 6: Additional FCM Tools
Lecture:
Module 6 pdf
Module 6 mp4